Udemy - A deep understanding of deep learning (with Python intro) 2-2023 - 磁力管家

BT种子名称

分享给好友

BT种子基本信息

种子哈希：a5bc60d3352ffbcdd147b039e824db1a6d31bb7a
文档大小：25.4 GB
文档个数：792个文档
下载次数：520次
下载速度：极快
收录时间：2024-05-07
最近下载：2025-05-16
DMCA/屏蔽：DMCA/屏蔽

下载磁力链接

magnet:?xt=urn:btih:A5BC60D3352FFBCDD147B039E824DB1A6D31BB7A
复制磁力链接到utorrent、Bitcomet、迅雷、115、百度网盘等下载工具进行下载。

下载BT种子

磁力链接种子下载迅雷下载二维码迅雷看看
磁力链接在线播放？试试百度云网盘离线下载播放！

Udemy - A deep understanding of deep learning (with Python intro) 2-2023的二维码

文档列表

19 - Understand and design CNNs/177 - Examine feature map activations.mp4 432.2 MB
22 - Style transfer/205 - Transferring the screaming bathtub.mp4 361.5 MB
19 - Understand and design CNNs/176 - Classify Gaussian blurs.mp4 293.3 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/218 - CodeChallenge sine wave extrapolation.mp4 272.5 MB
18 - Convolution and transformations/163 - Convolution in code.mp4 270.8 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/217 - Predicting alternating sequences.mp4 259.1 MB
26 - Where to go from here/229 - How to read academic DL papers.mp4 232.8 MB
19 - Understand and design CNNs/184 - The EMNIST dataset letter recognition.mp4 230.7 MB
19 - Understand and design CNNs/174 - CNN to classify MNIST digits.mp4 228.4 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/222 - Lorem ipsum.mp4 226.2 MB
7 - ANNs Artificial Neural Networks/52 - Multioutput ANN iris dataset.mp4 225.5 MB
23 - Generative adversarial networks/210 - CNN GAN with Gaussians.mp4 224.6 MB
21 - Transfer learning/200 - Pretraining with autoencoders.mp4 218.8 MB
19 - Understand and design CNNs/180 - Do autoencoders clean Gaussians.mp4 216.1 MB
9 - Regularization/72 - Dropout regularization in practice.mp4 211.2 MB
21 - Transfer learning/198 - Transfer learning with ResNet18.mp4 210.9 MB
16 - Autoencoders/157 - Autoencoder with tied weights.mp4 210.4 MB
7 - ANNs Artificial Neural Networks/47 - ANN for classifying qwerties.mp4 205.8 MB
10 - Metaparameters activations optimizers/82 - The wine quality dataset.mp4 203.8 MB
18 - Convolution and transformations/171 - Image transforms.mp4 202.3 MB
8 - Overfitting and crossvalidation/66 - Crossvalidation DataLoader.mp4 197.7 MB
23 - Generative adversarial networks/208 - Linear GAN with MNIST.mp4 197.3 MB
12 - More on data/119 - CodeChallenge unbalanced data.mp4 192.3 MB
16 - Autoencoders/156 - The latent code of MNIST.mp4 190.9 MB
11 - FFNs FeedForward Networks/107 - FFN to classify digits.mp4 187.0 MB
7 - ANNs Artificial Neural Networks/57 - Model depth vs breadth.mp4 186.0 MB
12 - More on data/123 - Data feature augmentation.mp4 184.8 MB
19 - Understand and design CNNs/178 - CodeChallenge Softcode internal parameters.mp4 184.6 MB
15 - Weight inits and investigations/147 - CodeChallenge Xavier vs Kaiming.mp4 177.3 MB
7 - ANNs Artificial Neural Networks/48 - Learning rates comparison.mp4 176.8 MB
21 - Transfer learning/201 - CIFAR10 with autoencoderpretrained model.mp4 175.0 MB
13 - Measuring model performance/131 - APRF example 1 wine quality.mp4 170.6 MB
15 - Weight inits and investigations/150 - Learningrelated changes in weights.mp4 169.4 MB
10 - Metaparameters activations optimizers/83 - CodeChallenge Minibatch size in the wine dataset.mp4 168.2 MB
7 - ANNs Artificial Neural Networks/49 - Multilayer ANN.mp4 168.0 MB
8 - Overfitting and crossvalidation/65 - Crossvalidation scikitlearn.mp4 167.3 MB
14 - FFN milestone projects/139 - Project 2 My solution.mp4 163.3 MB
19 - Understand and design CNNs/182 - CodeChallenge Custom loss functions.mp4 162.4 MB
10 - Metaparameters activations optimizers/95 - Loss functions in PyTorch.mp4 162.2 MB
18 - Convolution and transformations/172 - Creating and using custom DataLoaders.mp4 161.6 MB
9 - Regularization/71 - Dropout regularization.mp4 159.3 MB
12 - More on data/117 - Anatomy of a torch dataset and dataloader.mp4 159.2 MB
6 - Gradient descent/36 - Parametric experiments on gd.mp4 158.8 MB
13 - Measuring model performance/132 - APRF example 2 MNIST.mp4 157.6 MB
7 - ANNs Artificial Neural Networks/46 - CodeChallenge manipulate regression slopes.mp4 157.5 MB
12 - More on data/118 - Data size and network size.mp4 156.8 MB
7 - ANNs Artificial Neural Networks/55 - Depth vs breadth number of parameters.mp4 156.3 MB
15 - Weight inits and investigations/146 - Xavier and Kaiming initializations.mp4 156.1 MB
16 - Autoencoders/154 - CodeChallenge How many units.mp4 155.6 MB
19 - Understand and design CNNs/179 - CodeChallenge How wide the FC.mp4 151.7 MB
11 - FFNs FeedForward Networks/110 - Distributions of weights pre and postlearning.mp4 148.7 MB
11 - FFNs FeedForward Networks/111 - CodeChallenge MNIST and breadth vs depth.mp4 147.2 MB
12 - More on data/126 - Save the bestperforming model.mp4 146.7 MB
16 - Autoencoders/155 - AEs for occlusion.mp4 144.9 MB
15 - Weight inits and investigations/149 - Freezing weights during learning.mp4 144.5 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/220 - GRU and LSTM.mp4 144.2 MB
19 - Understand and design CNNs/183 - Discover the Gaussian parameters.mp4 143.3 MB
12 - More on data/121 - Data oversampling in MNIST.mp4 142.7 MB
11 - FFNs FeedForward Networks/106 - The MNIST dataset.mp4 142.3 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/216 - The RNN class in PyTorch.mp4 141.2 MB
10 - Metaparameters activations optimizers/93 - CodeChallenge Predict sugar.mp4 140.8 MB
16 - Autoencoders/153 - Denoising MNIST.mp4 140.7 MB
15 - Weight inits and investigations/143 - A surprising demo of weight initializations.mp4 139.2 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/221 - The LSTM and GRU classes.mp4 138.9 MB
21 - Transfer learning/196 - CodeChallenge letters to numbers.mp4 138.3 MB
6 - Gradient descent/32 - Gradient descent in 1D.mp4 137.8 MB
9 - Regularization/80 - CodeChallenge Effects of minibatch size.mp4 136.7 MB
20 - CNN milestone projects/190 - Project 1 My solution.mp4 136.3 MB
19 - Understand and design CNNs/181 - CodeChallenge AEs and occluded Gaussians.mp4 134.3 MB
7 - ANNs Artificial Neural Networks/53 - CodeChallenge more qwerties.mp4 133.3 MB
3 - Concepts in deep learning/7 - The role of DL in science and knowledge.mp4 133.3 MB
6 - Gradient descent/37 - CodeChallenge fixed vs dynamic learning rate.mp4 132.3 MB
18 - Convolution and transformations/161 - Convolution concepts.mp4 132.2 MB
9 - Regularization/75 - L2 regularization in practice.mp4 129.3 MB
21 - Transfer learning/195 - Transfer learning MNIST FMNIST.mp4 127.2 MB
10 - Metaparameters activations optimizers/89 - Activation functions.mp4 126.9 MB
9 - Regularization/78 - Batch training in action.mp4 126.1 MB
12 - More on data/122 - Data noise augmentation with devsettest.mp4 123.4 MB
18 - Convolution and transformations/165 - The Conv2 class in PyTorch.mp4 118.9 MB
15 - Weight inits and investigations/145 - CodeChallenge Weight variance inits.mp4 118.3 MB
10 - Metaparameters activations optimizers/91 - Activation functions comparison.mp4 118.2 MB
30 - Python intro Flow control/257 - Function error checking and handling.mp4 117.1 MB
13 - Measuring model performance/134 - Computation time.mp4 115.8 MB
9 - Regularization/76 - L1 regularization in practice.mp4 115.4 MB
10 - Metaparameters activations optimizers/96 - More practice with multioutput ANNs.mp4 115.3 MB
14 - FFN milestone projects/137 - Project 1 My solution.mp4 114.9 MB
8 - Overfitting and crossvalidation/64 - Crossvalidation manual separation.mp4 114.0 MB
15 - Weight inits and investigations/144 - Theory Why and how to initialize weights.mp4 113.2 MB
10 - Metaparameters activations optimizers/103 - Learning rate decay.mp4 112.4 MB
7 - ANNs Artificial Neural Networks/45 - ANN for regression.mp4 110.4 MB
19 - Understand and design CNNs/185 - Dropout in CNNs.mp4 109.3 MB
11 - FFNs FeedForward Networks/109 - CodeChallenge Data normalization.mp4 109.2 MB
31 - Python intro Text and plots/263 - Images.mp4 109.2 MB
18 - Convolution and transformations/167 - Transpose convolution.mp4 107.8 MB
5 - Math numpy PyTorch/19 - Softmax.mp4 106.3 MB
10 - Metaparameters activations optimizers/90 - Activation functions in PyTorch.mp4 106.2 MB
19 - Understand and design CNNs/187 - CodeChallenge Varying number of channels.mp4 104.7 MB
7 - ANNs Artificial Neural Networks/56 - Defining models using sequential vs class.mp4 102.6 MB
10 - Metaparameters activations optimizers/100 - Optimizers comparison.mp4 102.0 MB
6 - Gradient descent/34 - Gradient descent in 2D.mp4 101.1 MB
10 - Metaparameters activations optimizers/94 - Loss functions.mp4 100.9 MB
15 - Weight inits and investigations/148 - CodeChallenge Identically random weights.mp4 100.8 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/219 - More on RNNs Hidden states embeddings.mp4 98.8 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/214 - Leveraging sequences in deep learning.mp4 96.1 MB
13 - Measuring model performance/133 - CodeChallenge MNIST with unequal groups.mp4 95.9 MB
29 - Python intro Functions/242 - Python libraries pandas.mp4 95.7 MB
13 - Measuring model performance/129 - Accuracy precision recall F1.mp4 95.1 MB
15 - Weight inits and investigations/142 - Explanation of weight matrix sizes.mp4 93.9 MB
9 - Regularization/69 - Regularization Concept and methods.mp4 92.9 MB
29 - Python intro Functions/247 - Classes and objectoriented programming.mp4 92.8 MB
25 - Ethics of deep learning/227 - Accountability and making ethical AI.mp4 92.7 MB
5 - Math numpy PyTorch/26 - The ttest.mp4 92.5 MB
31 - Python intro Text and plots/261 - Making the graphs look nicer.mp4 91.3 MB
8 - Overfitting and crossvalidation/67 - Splitting data into train devset test.mp4 91.2 MB
23 - Generative adversarial networks/209 - CodeChallenge Linear GAN with FMNIST.mp4 90.7 MB
11 - FFNs FeedForward Networks/114 - Shifted MNIST.mp4 90.6 MB
6 - Gradient descent/33 - CodeChallenge unfortunate starting value.mp4 90.1 MB
5 - Math numpy PyTorch/21 - Entropy and crossentropy.mp4 89.5 MB
3 - Concepts in deep learning/9 - Are artificial neurons like biological neurons.mp4 89.3 MB
25 - Ethics of deep learning/225 - Some other possible ethical scenarios.mp4 88.4 MB
23 - Generative adversarial networks/211 - CodeChallenge Gaussians with fewer layers.mp4 88.4 MB
14 - FFN milestone projects/141 - Project 3 My solution.mp4 87.6 MB
18 - Convolution and transformations/162 - Feature maps and convolution kernels.mp4 87.3 MB
9 - Regularization/79 - The importance of equal batch sizes.mp4 86.1 MB
22 - Style transfer/206 - CodeChallenge Style transfer with AlexNet.mp4 85.4 MB
11 - FFNs FeedForward Networks/115 - CodeChallenge The mystery of the missing 7.mp4 84.8 MB
8 - Overfitting and crossvalidation/61 - What is overfitting and is it as bad as they say.mp4 80.7 MB
7 - ANNs Artificial Neural Networks/60 - Reflection Are DL models understandable yet.mp4 80.5 MB
20 - CNN milestone projects/193 - Project 4 Psychometric functions in CNNs.mp4 80.2 MB
30 - Python intro Flow control/249 - Ifelse statements part 2.mp4 80.0 MB
5 - Math numpy PyTorch/25 - Reproducible randomness via seeding.mp4 79.2 MB
3 - Concepts in deep learning/8 - Running experiments to understand DL.mp4 78.5 MB
23 - Generative adversarial networks/212 - CNN GAN with FMNIST.mp4 78.3 MB
10 - Metaparameters activations optimizers/85 - The importance of data normalization.mp4 76.3 MB
18 - Convolution and transformations/170 - To pool or to stride.mp4 74.2 MB
31 - Python intro Text and plots/260 - Subplot geometry.mp4 73.8 MB
10 - Metaparameters activations optimizers/87 - Batch normalization in practice.mp4 73.4 MB
23 - Generative adversarial networks/213 - CodeChallenge CNN GAN with CIFAR.mp4 72.9 MB
18 - Convolution and transformations/168 - Maxmean pooling.mp4 72.7 MB
17 - Running models on a GPU/158 - What is a GPU and why use it.mp4 72.6 MB
31 - Python intro Text and plots/258 - Printing and string interpolation.mp4 72.4 MB
5 - Math numpy PyTorch/22 - Minmax and argminargmax.mp4 72.3 MB
30 - Python intro Flow control/255 - while loops.mp4 71.7 MB
8 - Overfitting and crossvalidation/62 - Crossvalidation.mp4 71.6 MB
30 - Python intro Flow control/253 - Initializing variables.mp4 70.7 MB
5 - Math numpy PyTorch/18 - Matrix multiplication.mp4 70.0 MB
22 - Style transfer/203 - The Gram matrix feature activation covariance.mp4 69.7 MB
9 - Regularization/74 - Weight regularization L1L2 math.mp4 68.6 MB
10 - Metaparameters activations optimizers/88 - CodeChallenge Batchnormalize the qwerties.mp4 68.0 MB
27 - Python intro Data types/236 - Booleans.mp4 67.7 MB
5 - Math numpy PyTorch/13 - Spectral theories in mathematics.mp4 67.6 MB
30 - Python intro Flow control/250 - For loops.mp4 67.5 MB
18 - Convolution and transformations/169 - Pooling in PyTorch.mp4 67.4 MB
10 - Metaparameters activations optimizers/92 - CodeChallenge Compare relu variants.mp4 67.1 MB
19 - Understand and design CNNs/175 - CNN on shifted MNIST.mp4 66.6 MB
5 - Math numpy PyTorch/24 - Random sampling and sampling variability.mp4 66.3 MB
10 - Metaparameters activations optimizers/84 - Data normalization.mp4 65.5 MB
25 - Ethics of deep learning/224 - Example case studies.mp4 65.4 MB
10 - Metaparameters activations optimizers/98 - SGD with momentum.mp4 65.1 MB
30 - Python intro Flow control/254 - Singleline loops list comprehension.mp4 64.9 MB
12 - More on data/125 - Save and load trained models.mp4 64.6 MB
10 - Metaparameters activations optimizers/102 - CodeChallenge Adam with L2 regularization.mp4 64.1 MB
13 - Measuring model performance/130 - APRF in code.mp4 64.0 MB
9 - Regularization/73 - Dropout example 2.mp4 63.7 MB
17 - Running models on a GPU/159 - Implementation.mp4 63.6 MB
19 - Understand and design CNNs/186 - CodeChallenge How low can you go.mp4 63.2 MB
11 - FFNs FeedForward Networks/113 - Scrambled MNIST.mp4 63.1 MB
10 - Metaparameters activations optimizers/97 - Optimizers minibatch momentum.mp4 62.3 MB
17 - Running models on a GPU/160 - CodeChallenge Run an experiment on the GPU.mp4 62.0 MB
30 - Python intro Flow control/251 - Enumerate and zip.mp4 61.4 MB
21 - Transfer learning/194 - Transfer learning What why and when.mp4 61.0 MB
27 - Python intro Data types/231 - Variables.mp4 60.6 MB
23 - Generative adversarial networks/207 - GAN What why and how.mp4 60.3 MB
29 - Python intro Functions/244 - Creating functions.mp4 60.1 MB
7 - ANNs Artificial Neural Networks/58 - CodeChallenge convert sequential to class.mp4 59.9 MB
31 - Python intro Text and plots/264 - Export plots in low and high resolution.mp4 59.0 MB
1 - Introduction/1 - How to learn from this course.mp4 57.6 MB
29 - Python intro Functions/245 - Global and local variable scopes.mp4 57.5 MB
7 - ANNs Artificial Neural Networks/50 - Linear solutions to linear problems.mp4 57.2 MB
10 - Metaparameters activations optimizers/86 - Batch normalization.mp4 57.1 MB
10 - Metaparameters activations optimizers/101 - CodeChallenge Optimizers and something.mp4 57.0 MB
6 - Gradient descent/30 - Overview of gradient descent.mp4 57.0 MB
20 - CNN milestone projects/189 - Project 1 Import and classify CIFAR10.mp4 55.8 MB
25 - Ethics of deep learning/226 - Will deep learning take our jobs.mp4 55.6 MB
2 - Download all course materials/3 - Downloading and using the code.mp4 55.1 MB
10 - Metaparameters activations optimizers/99 - Optimizers RMSprop Adam.mp4 55.1 MB
30 - Python intro Flow control/256 - Broadcasting in numpy.mp4 55.0 MB
7 - ANNs Artificial Neural Networks/43 - ANN math part 2 errors loss cost.mp4 54.7 MB
27 - Python intro Data types/232 - Math and printing.mp4 53.6 MB
3 - Concepts in deep learning/6 - How models learn.mp4 53.6 MB
31 - Python intro Text and plots/262 - Seaborn.mp4 53.4 MB
7 - ANNs Artificial Neural Networks/40 - The perceptron and ANN architecture.mp4 53.2 MB
11 - FFNs FeedForward Networks/112 - CodeChallenge Optimizers and MNIST.mp4 53.2 MB
7 - ANNs Artificial Neural Networks/54 - Comparing the number of hidden units.mp4 51.8 MB
12 - More on data/124 - Getting data into colab.mp4 51.1 MB
5 - Math numpy PyTorch/23 - Mean and variance.mp4 49.3 MB
5 - Math numpy PyTorch/27 - Derivatives intuition and polynomials.mp4 48.5 MB
12 - More on data/127 - Where to find online datasets.mp4 48.3 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/215 - How RNNs work.mp4 47.9 MB
20 - CNN milestone projects/191 - Project 2 CIFARautoencoder.mp4 47.4 MB
11 - FFNs FeedForward Networks/108 - CodeChallenge Binarized MNIST images.mp4 46.7 MB
7 - ANNs Artificial Neural Networks/42 - ANN math part 1 forward prop.mp4 46.1 MB
6 - Gradient descent/35 - CodeChallenge 2D gradient ascent.mp4 45.5 MB
30 - Python intro Flow control/248 - Ifelse statements.mp4 45.3 MB
7 - ANNs Artificial Neural Networks/41 - A geometric view of ANNs.mp4 45.0 MB
8 - Overfitting and crossvalidation/68 - Crossvalidation on regression.mp4 43.1 MB
22 - Style transfer/204 - The style transfer algorithm.mp4 42.7 MB
3 - Concepts in deep learning/5 - What is an artificial neural network.mp4 42.0 MB
31 - Python intro Text and plots/259 - Plotting dots and lines.mp4 42.0 MB
28 - Python intro Indexing slicing/239 - Slicing.mp4 41.9 MB
29 - Python intro Functions/241 - Python libraries numpy.mp4 41.8 MB
18 - Convolution and transformations/164 - Convolution parameters stride padding.mp4 40.8 MB
6 - Gradient descent/31 - What about local minima.mp4 39.9 MB
1 - Introduction/2 - Using Udemy like a pro.mp4 39.9 MB
7 - ANNs Artificial Neural Networks/44 - ANN math part 3 backprop.mp4 39.4 MB
14 - FFN milestone projects/136 - Project 1 A gratuitously complex adding machine.mp4 39.2 MB
29 - Python intro Functions/243 - Getting help on functions.mp4 39.1 MB
25 - Ethics of deep learning/223 - Will AI save us or destroy us.mp4 39.0 MB
5 - Math numpy PyTorch/29 - Derivatives product and chain rules.mp4 38.8 MB
10 - Metaparameters activations optimizers/104 - How to pick the right metaparameters.mp4 38.6 MB
14 - FFN milestone projects/138 - Project 2 Predicting heart disease.mp4 37.3 MB
9 - Regularization/77 - Training in minibatches.mp4 37.1 MB
27 - Python intro Data types/233 - Lists 1 of 2.mp4 36.8 MB
11 - FFNs FeedForward Networks/116 - Universal approximation theorem.mp4 35.9 MB
27 - Python intro Data types/234 - Lists 2 of 2.mp4 35.1 MB
19 - Understand and design CNNs/173 - The canonical CNN architecture.mp4 34.8 MB
27 - Python intro Data types/237 - Dictionaries.mp4 34.6 MB
21 - Transfer learning/197 - Famous CNN architectures.mp4 34.6 MB
28 - Python intro Indexing slicing/238 - Indexing.mp4 34.5 MB
6 - Gradient descent/38 - Vanishing and exploding gradients.mp4 33.2 MB
18 - Convolution and transformations/166 - CodeChallenge Choose the parameters.mp4 32.5 MB
12 - More on data/120 - What to do about unbalanced designs.mp4 31.2 MB
16 - Autoencoders/152 - What are autoencoders and what do they do.mp4 30.8 MB
5 - Math numpy PyTorch/20 - Logarithms.mp4 30.6 MB
20 - CNN milestone projects/192 - Project 3 FMNIST.mp4 30.2 MB
5 - Math numpy PyTorch/17 - OMG its the dot product.mp4 30.1 MB
22 - Style transfer/202 - What is style transfer and how does it work.mp4 29.5 MB
14 - FFN milestone projects/140 - Project 3 FFN for missing data interpolation.mp4 28.7 MB
7 - ANNs Artificial Neural Networks/51 - Why multilayer linear models dont exist.mp4 28.5 MB
13 - Measuring model performance/128 - Two perspectives of the world.mp4 28.1 MB
13 - Measuring model performance/135 - Better performance in test than train.mp4 27.5 MB
5 - Math numpy PyTorch/16 - Vector and matrix transpose.mp4 27.4 MB
5 - Math numpy PyTorch/28 - Derivatives find minima.mp4 27.3 MB
26 - Where to go from here/228 - How to learn topic X in deep learning.mp4 26.5 MB
6 - Gradient descent/39 - Tangent Notebook revision history.mp4 26.4 MB
9 - Regularization/70 - train and eval modes.mp4 23.9 MB
5 - Math numpy PyTorch/14 - Terms and datatypes in math and computers.mp4 23.8 MB
27 - Python intro Data types/235 - Tuples.mp4 23.3 MB
30 - Python intro Flow control/252 - Continue.mp4 21.7 MB
21 - Transfer learning/199 - CodeChallenge VGG16.mp4 21.3 MB
5 - Math numpy PyTorch/15 - Converting reality to numbers.mp4 20.7 MB
29 - Python intro Functions/240 - Inputs and outputs.mp4 20.1 MB
8 - Overfitting and crossvalidation/63 - Generalization.mp4 19.9 MB
10 - Metaparameters activations optimizers/81 - What are metaparameters.mp4 19.6 MB
11 - FFNs FeedForward Networks/105 - What are fullyconnected and feedforward networks.mp4 18.7 MB
27 - Python intro Data types/230 - How to learn from the Python tutorial.mp4 18.4 MB
15 - Weight inits and investigations/151 - Use default inits or apply your own.mp4 17.6 MB
29 - Python intro Functions/246 - Copies and referents of variables.mp4 15.8 MB
4 - About the Python tutorial/10 - Should you watch the Python tutorial.mp4 14.5 MB
19 - Understand and design CNNs/188 - So many possibilities How to create a CNN.mp4 13.6 MB
5 - Math numpy PyTorch/12 - Introduction to this section.mp4 6.9 MB
2 - Download all course materials/4 - My policy on codesharing.mp4 5.9 MB
2 - Download all course materials/3 - DUDL-PythonCode.zip 1.4 MB
19 - Understand and design CNNs/177 - Examine feature map activations Vietnamese.vtt 45.1 kB
7 - ANNs Artificial Neural Networks/52 - Multioutput ANN iris dataset Vietnamese.vtt 43.7 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/218 - CodeChallenge sine wave extrapolation Vietnamese.vtt 42.8 kB
19 - Understand and design CNNs/174 - CNN to classify MNIST digits Vietnamese.vtt 41.7 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/222 - Lorem ipsum Vietnamese.vtt 40.7 kB
7 - ANNs Artificial Neural Networks/45 - ANN for regression Vietnamese.vtt 40.4 kB
7 - ANNs Artificial Neural Networks/48 - Learning rates comparison Vietnamese.vtt 40.3 kB
19 - Understand and design CNNs/184 - The EMNIST dataset letter recognition Vietnamese.vtt 39.5 kB
16 - Autoencoders/157 - Autoencoder with tied weights Vietnamese.vtt 39.3 kB
7 - ANNs Artificial Neural Networks/47 - ANN for classifying qwerties Vietnamese.vtt 38.4 kB
19 - Understand and design CNNs/176 - Classify Gaussian blurs Vietnamese.vtt 37.4 kB
9 - Regularization/72 - Dropout regularization in practice Vietnamese.vtt 37.2 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/220 - GRU and LSTM Vietnamese.vtt 36.4 kB
11 - FFNs FeedForward Networks/107 - FFN to classify digits Vietnamese.vtt 36.3 kB
9 - Regularization/71 - Dropout regularization Vietnamese.vtt 36.1 kB
19 - Understand and design CNNs/177 - Examine feature map activations English.vtt 35.8 kB
15 - Weight inits and investigations/150 - Learningrelated changes in weights Vietnamese.vtt 35.7 kB
23 - Generative adversarial networks/208 - Linear GAN with MNIST Vietnamese.vtt 35.6 kB
22 - Style transfer/205 - Transferring the screaming bathtub Vietnamese.vtt 35.5 kB
7 - ANNs Artificial Neural Networks/52 - Multioutput ANN iris dataset English.vtt 35.4 kB
18 - Convolution and transformations/161 - Convolution concepts Vietnamese.vtt 35.4 kB
8 - Overfitting and crossvalidation/65 - Crossvalidation scikitlearn Vietnamese.vtt 34.9 kB
16 - Autoencoders/156 - The latent code of MNIST Vietnamese.vtt 34.6 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/218 - CodeChallenge sine wave extrapolation English.vtt 34.4 kB
29 - Python intro Functions/244 - Creating functions Vietnamese.vtt 34.0 kB
18 - Convolution and transformations/163 - Convolution in code Vietnamese.vtt 33.7 kB
7 - ANNs Artificial Neural Networks/57 - Model depth vs breadth Vietnamese.vtt 33.7 kB
19 - Understand and design CNNs/174 - CNN to classify MNIST digits English.vtt 33.6 kB
8 - Overfitting and crossvalidation/66 - Crossvalidation DataLoader Vietnamese.vtt 33.5 kB
21 - Transfer learning/200 - Pretraining with autoencoders Vietnamese.vtt 33.3 kB
12 - More on data/119 - CodeChallenge unbalanced data Vietnamese.vtt 33.2 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/222 - Lorem ipsum English.vtt 33.0 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/217 - Predicting alternating sequences Vietnamese.vtt 32.8 kB
19 - Understand and design CNNs/182 - CodeChallenge Custom loss functions Vietnamese.vtt 32.4 kB
7 - ANNs Artificial Neural Networks/48 - Learning rates comparison English.vtt 31.9 kB
19 - Understand and design CNNs/184 - The EMNIST dataset letter recognition English.vtt 31.8 kB
7 - ANNs Artificial Neural Networks/45 - ANN for regression English.vtt 31.7 kB
7 - ANNs Artificial Neural Networks/49 - Multilayer ANN Vietnamese.vtt 31.6 kB
12 - More on data/123 - Data feature augmentation Vietnamese.vtt 31.5 kB
16 - Autoencoders/154 - CodeChallenge How many units Vietnamese.vtt 31.5 kB
7 - ANNs Artificial Neural Networks/46 - CodeChallenge manipulate regression slopes Vietnamese.vtt 31.3 kB
7 - ANNs Artificial Neural Networks/40 - The perceptron and ANN architecture Vietnamese.vtt 31.3 kB
10 - Metaparameters activations optimizers/97 - Optimizers minibatch momentum Vietnamese.vtt 31.3 kB
16 - Autoencoders/157 - Autoencoder with tied weights English.vtt 30.7 kB
6 - Gradient descent/36 - Parametric experiments on gd Vietnamese.vtt 30.6 kB
14 - FFN milestone projects/139 - Project 2 My solution Vietnamese.vtt 30.5 kB
7 - ANNs Artificial Neural Networks/47 - ANN for classifying qwerties English.vtt 30.4 kB
30 - Python intro Flow control/255 - while loops Vietnamese.vtt 30.4 kB
19 - Understand and design CNNs/176 - Classify Gaussian blurs English.vtt 30.4 kB
18 - Convolution and transformations/172 - Creating and using custom DataLoaders Vietnamese.vtt 30.1 kB
27 - Python intro Data types/236 - Booleans Vietnamese.vtt 30.1 kB
18 - Convolution and transformations/168 - Maxmean pooling Vietnamese.vtt 30.0 kB
27 - Python intro Data types/231 - Variables Vietnamese.vtt 30.0 kB
5 - Math numpy PyTorch/19 - Softmax Vietnamese.vtt 29.9 kB
31 - Python intro Text and plots/261 - Making the graphs look nicer Vietnamese.vtt 29.9 kB
29 - Python intro Functions/247 - Classes and objectoriented programming Vietnamese.vtt 29.8 kB
12 - More on data/117 - Anatomy of a torch dataset and dataloader Vietnamese.vtt 29.7 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/216 - The RNN class in PyTorch Vietnamese.vtt 29.7 kB
9 - Regularization/74 - Weight regularization L1L2 math Vietnamese.vtt 29.7 kB
10 - Metaparameters activations optimizers/95 - Loss functions in PyTorch Vietnamese.vtt 29.6 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/220 - GRU and LSTM English.vtt 29.6 kB
9 - Regularization/72 - Dropout regularization in practice English.vtt 29.5 kB
30 - Python intro Flow control/253 - Initializing variables Vietnamese.vtt 29.3 kB
27 - Python intro Data types/232 - Math and printing Vietnamese.vtt 29.1 kB
21 - Transfer learning/201 - CIFAR10 with autoencoderpretrained model Vietnamese.vtt 29.0 kB
11 - FFNs FeedForward Networks/107 - FFN to classify digits English.vtt 29.0 kB
15 - Weight inits and investigations/150 - Learningrelated changes in weights English.vtt 29.0 kB
10 - Metaparameters activations optimizers/89 - Activation functions Vietnamese.vtt 28.9 kB
10 - Metaparameters activations optimizers/82 - The wine quality dataset Vietnamese.vtt 28.9 kB
26 - Where to go from here/229 - How to read academic DL papers Vietnamese.vtt 28.8 kB
18 - Convolution and transformations/161 - Convolution concepts English.vtt 28.6 kB
8 - Overfitting and crossvalidation/62 - Crossvalidation Vietnamese.vtt 28.6 kB
22 - Style transfer/205 - Transferring the screaming bathtub English.vtt 28.4 kB
10 - Metaparameters activations optimizers/93 - CodeChallenge Predict sugar Vietnamese.vtt 28.4 kB
16 - Autoencoders/155 - AEs for occlusion Vietnamese.vtt 28.4 kB
30 - Python intro Flow control/257 - Function error checking and handling Vietnamese.vtt 28.2 kB
23 - Generative adversarial networks/208 - Linear GAN with MNIST English.vtt 28.2 kB
31 - Python intro Text and plots/263 - Images Vietnamese.vtt 28.1 kB
3 - Concepts in deep learning/9 - Are artificial neurons like biological neurons Vietnamese.vtt 28.1 kB
9 - Regularization/71 - Dropout regularization English.vtt 28.0 kB
7 - ANNs Artificial Neural Networks/55 - Depth vs breadth number of parameters Vietnamese.vtt 28.0 kB
16 - Autoencoders/156 - The latent code of MNIST English.vtt 28.0 kB
19 - Understand and design CNNs/178 - CodeChallenge Softcode internal parameters Vietnamese.vtt 27.7 kB
21 - Transfer learning/194 - Transfer learning What why and when Vietnamese.vtt 27.7 kB
5 - Math numpy PyTorch/21 - Entropy and crossentropy Vietnamese.vtt 27.7 kB
15 - Weight inits and investigations/147 - CodeChallenge Xavier vs Kaiming Vietnamese.vtt 27.6 kB
30 - Python intro Flow control/250 - For loops Vietnamese.vtt 27.6 kB
11 - FFNs FeedForward Networks/109 - CodeChallenge Data normalization Vietnamese.vtt 27.4 kB
6 - Gradient descent/32 - Gradient descent in 1D Vietnamese.vtt 27.3 kB
7 - ANNs Artificial Neural Networks/57 - Model depth vs breadth English.vtt 27.3 kB
15 - Weight inits and investigations/143 - A surprising demo of weight initializations Vietnamese.vtt 27.2 kB
29 - Python intro Functions/244 - Creating functions English.vtt 27.1 kB
21 - Transfer learning/198 - Transfer learning with ResNet18 Vietnamese.vtt 27.1 kB
12 - More on data/121 - Data oversampling in MNIST Vietnamese.vtt 27.1 kB
18 - Convolution and transformations/163 - Convolution in code English.vtt 27.0 kB
31 - Python intro Text and plots/258 - Printing and string interpolation Vietnamese.vtt 27.0 kB
19 - Understand and design CNNs/180 - Do autoencoders clean Gaussians Vietnamese.vtt 26.9 kB
8 - Overfitting and crossvalidation/65 - Crossvalidation scikitlearn English.vtt 26.9 kB
23 - Generative adversarial networks/207 - GAN What why and how Vietnamese.vtt 26.9 kB
18 - Convolution and transformations/171 - Image transforms Vietnamese.vtt 26.8 kB
3 - Concepts in deep learning/7 - The role of DL in science and knowledge Vietnamese.vtt 26.5 kB
19 - Understand and design CNNs/182 - CodeChallenge Custom loss functions English.vtt 26.4 kB
10 - Metaparameters activations optimizers/94 - Loss functions Vietnamese.vtt 26.2 kB
10 - Metaparameters activations optimizers/83 - CodeChallenge Minibatch size in the wine dataset Vietnamese.vtt 26.0 kB
7 - ANNs Artificial Neural Networks/49 - Multilayer ANN English.vtt 25.9 kB
12 - More on data/118 - Data size and network size Vietnamese.vtt 25.9 kB
31 - Python intro Text and plots/260 - Subplot geometry Vietnamese.vtt 25.9 kB
12 - More on data/119 - CodeChallenge unbalanced data English.vtt 25.9 kB
6 - Gradient descent/37 - CodeChallenge fixed vs dynamic learning rate Vietnamese.vtt 25.8 kB
16 - Autoencoders/154 - CodeChallenge How many units English.vtt 25.6 kB
5 - Math numpy PyTorch/27 - Derivatives intuition and polynomials Vietnamese.vtt 25.6 kB
21 - Transfer learning/200 - Pretraining with autoencoders English.vtt 25.5 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/217 - Predicting alternating sequences English.vtt 25.5 kB
19 - Understand and design CNNs/183 - Discover the Gaussian parameters Vietnamese.vtt 25.5 kB
30 - Python intro Flow control/249 - Ifelse statements part 2 Vietnamese.vtt 25.4 kB
8 - Overfitting and crossvalidation/66 - Crossvalidation DataLoader English.vtt 25.3 kB
5 - Math numpy PyTorch/23 - Mean and variance Vietnamese.vtt 25.3 kB
15 - Weight inits and investigations/146 - Xavier and Kaiming initializations Vietnamese.vtt 25.2 kB
12 - More on data/123 - Data feature augmentation English.vtt 25.2 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/219 - More on RNNs Hidden states embeddings Vietnamese.vtt 25.1 kB
7 - ANNs Artificial Neural Networks/46 - CodeChallenge manipulate regression slopes English.vtt 25.0 kB
16 - Autoencoders/153 - Denoising MNIST Vietnamese.vtt 25.0 kB
12 - More on data/126 - Save the bestperforming model Vietnamese.vtt 24.9 kB
7 - ANNs Artificial Neural Networks/40 - The perceptron and ANN architecture English.vtt 24.8 kB
10 - Metaparameters activations optimizers/99 - Optimizers RMSprop Adam Vietnamese.vtt 24.7 kB
30 - Python intro Flow control/255 - while loops English.vtt 24.6 kB
5 - Math numpy PyTorch/19 - Softmax English.vtt 24.6 kB
7 - ANNs Artificial Neural Networks/42 - ANN math part 1 forward prop Vietnamese.vtt 24.5 kB
11 - FFNs FeedForward Networks/110 - Distributions of weights pre and postlearning Vietnamese.vtt 24.5 kB
14 - FFN milestone projects/139 - Project 2 My solution English.vtt 24.4 kB
10 - Metaparameters activations optimizers/97 - Optimizers minibatch momentum English.vtt 24.4 kB
23 - Generative adversarial networks/210 - CNN GAN with Gaussians Vietnamese.vtt 24.3 kB
17 - Running models on a GPU/158 - What is a GPU and why use it Vietnamese.vtt 24.3 kB
30 - Python intro Flow control/254 - Singleline loops list comprehension Vietnamese.vtt 24.2 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/215 - How RNNs work Vietnamese.vtt 24.2 kB
27 - Python intro Data types/236 - Booleans English.vtt 24.2 kB
6 - Gradient descent/36 - Parametric experiments on gd English.vtt 24.1 kB
9 - Regularization/74 - Weight regularization L1L2 math English.vtt 24.0 kB
27 - Python intro Data types/231 - Variables English.vtt 23.9 kB
21 - Transfer learning/196 - CodeChallenge letters to numbers Vietnamese.vtt 23.9 kB
3 - Concepts in deep learning/5 - What is an artificial neural network Vietnamese.vtt 23.8 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/216 - The RNN class in PyTorch English.vtt 23.8 kB
31 - Python intro Text and plots/261 - Making the graphs look nicer English.vtt 23.8 kB
10 - Metaparameters activations optimizers/95 - Loss functions in PyTorch English.vtt 23.7 kB
18 - Convolution and transformations/168 - Maxmean pooling English.vtt 23.7 kB
30 - Python intro Flow control/248 - Ifelse statements Vietnamese.vtt 23.6 kB
10 - Metaparameters activations optimizers/89 - Activation functions English.vtt 23.6 kB
30 - Python intro Flow control/256 - Broadcasting in numpy Vietnamese.vtt 23.5 kB
29 - Python intro Functions/247 - Classes and objectoriented programming English.vtt 23.5 kB
27 - Python intro Data types/232 - Math and printing English.vtt 23.5 kB
18 - Convolution and transformations/172 - Creating and using custom DataLoaders English.vtt 23.4 kB
12 - More on data/117 - Anatomy of a torch dataset and dataloader English.vtt 23.2 kB
6 - Gradient descent/34 - Gradient descent in 2D Vietnamese.vtt 23.1 kB
21 - Transfer learning/201 - CIFAR10 with autoencoderpretrained model English.vtt 23.0 kB
10 - Metaparameters activations optimizers/82 - The wine quality dataset English.vtt 22.8 kB
6 - Gradient descent/30 - Overview of gradient descent Vietnamese.vtt 22.8 kB
7 - ANNs Artificial Neural Networks/55 - Depth vs breadth number of parameters English.vtt 22.7 kB
30 - Python intro Flow control/253 - Initializing variables English.vtt 22.6 kB
31 - Python intro Text and plots/263 - Images English.vtt 22.6 kB
27 - Python intro Data types/233 - Lists 1 of 2 Vietnamese.vtt 22.5 kB
16 - Autoencoders/155 - AEs for occlusion English.vtt 22.5 kB
29 - Python intro Functions/241 - Python libraries numpy Vietnamese.vtt 22.5 kB
5 - Math numpy PyTorch/21 - Entropy and crossentropy English.vtt 22.4 kB
26 - Where to go from here/229 - How to read academic DL papers English.vtt 22.4 kB
29 - Python intro Functions/242 - Python libraries pandas Vietnamese.vtt 22.4 kB
10 - Metaparameters activations optimizers/96 - More practice with multioutput ANNs Vietnamese.vtt 22.4 kB
30 - Python intro Flow control/257 - Function error checking and handling English.vtt 22.4 kB
5 - Math numpy PyTorch/18 - Matrix multiplication Vietnamese.vtt 22.3 kB
30 - Python intro Flow control/250 - For loops English.vtt 22.3 kB
19 - Understand and design CNNs/178 - CodeChallenge Softcode internal parameters English.vtt 22.3 kB
18 - Convolution and transformations/169 - Pooling in PyTorch Vietnamese.vtt 22.2 kB
8 - Overfitting and crossvalidation/62 - Crossvalidation English.vtt 22.2 kB
10 - Metaparameters activations optimizers/93 - CodeChallenge Predict sugar English.vtt 22.2 kB
10 - Metaparameters activations optimizers/84 - Data normalization Vietnamese.vtt 22.1 kB
13 - Measuring model performance/131 - APRF example 1 wine quality Vietnamese.vtt 22.0 kB
21 - Transfer learning/194 - Transfer learning What why and when English.vtt 22.0 kB
18 - Convolution and transformations/167 - Transpose convolution Vietnamese.vtt 21.9 kB
5 - Math numpy PyTorch/26 - The ttest Vietnamese.vtt 21.8 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/221 - The LSTM and GRU classes Vietnamese.vtt 21.8 kB
15 - Weight inits and investigations/147 - CodeChallenge Xavier vs Kaiming English.vtt 21.7 kB
6 - Gradient descent/32 - Gradient descent in 1D English.vtt 21.7 kB
11 - FFNs FeedForward Networks/109 - CodeChallenge Data normalization English.vtt 21.7 kB
19 - Understand and design CNNs/180 - Do autoencoders clean Gaussians English.vtt 21.7 kB
21 - Transfer learning/198 - Transfer learning with ResNet18 English.vtt 21.7 kB
15 - Weight inits and investigations/149 - Freezing weights during learning Vietnamese.vtt 21.6 kB
10 - Metaparameters activations optimizers/94 - Loss functions English.vtt 21.6 kB
3 - Concepts in deep learning/8 - Running experiments to understand DL Vietnamese.vtt 21.5 kB
19 - Understand and design CNNs/187 - CodeChallenge Varying number of channels Vietnamese.vtt 21.5 kB
5 - Math numpy PyTorch/27 - Derivatives intuition and polynomials English.vtt 21.5 kB
31 - Python intro Text and plots/258 - Printing and string interpolation English.vtt 21.5 kB
7 - ANNs Artificial Neural Networks/41 - A geometric view of ANNs Vietnamese.vtt 21.5 kB
3 - Concepts in deep learning/9 - Are artificial neurons like biological neurons English.vtt 21.5 kB
9 - Regularization/69 - Regularization Concept and methods Vietnamese.vtt 21.4 kB
12 - More on data/121 - Data oversampling in MNIST English.vtt 21.3 kB
9 - Regularization/75 - L2 regularization in practice Vietnamese.vtt 21.3 kB
29 - Python intro Functions/245 - Global and local variable scopes Vietnamese.vtt 21.3 kB
7 - ANNs Artificial Neural Networks/56 - Defining models using sequential vs class Vietnamese.vtt 21.3 kB
8 - Overfitting and crossvalidation/61 - What is overfitting and is it as bad as they say Vietnamese.vtt 21.2 kB
8 - Overfitting and crossvalidation/64 - Crossvalidation manual separation Vietnamese.vtt 21.2 kB
15 - Weight inits and investigations/143 - A surprising demo of weight initializations English.vtt 21.2 kB
3 - Concepts in deep learning/6 - How models learn Vietnamese.vtt 21.1 kB
23 - Generative adversarial networks/207 - GAN What why and how English.vtt 21.0 kB
18 - Convolution and transformations/171 - Image transforms English.vtt 21.0 kB
10 - Metaparameters activations optimizers/86 - Batch normalization Vietnamese.vtt 21.0 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/214 - Leveraging sequences in deep learning Vietnamese.vtt 20.9 kB
18 - Convolution and transformations/165 - The Conv2 class in PyTorch Vietnamese.vtt 20.9 kB
28 - Python intro Indexing slicing/238 - Indexing Vietnamese.vtt 20.9 kB
12 - More on data/118 - Data size and network size English.vtt 20.8 kB
3 - Concepts in deep learning/7 - The role of DL in science and knowledge English.vtt 20.8 kB
12 - More on data/122 - Data noise augmentation with devsettest Vietnamese.vtt 20.8 kB
19 - Understand and design CNNs/183 - Discover the Gaussian parameters English.vtt 20.7 kB
6 - Gradient descent/37 - CodeChallenge fixed vs dynamic learning rate English.vtt 20.7 kB
15 - Weight inits and investigations/145 - CodeChallenge Weight variance inits Vietnamese.vtt 20.6 kB
10 - Metaparameters activations optimizers/83 - CodeChallenge Minibatch size in the wine dataset English.vtt 20.5 kB
28 - Python intro Indexing slicing/239 - Slicing Vietnamese.vtt 20.4 kB
5 - Math numpy PyTorch/22 - Minmax and argminargmax Vietnamese.vtt 20.4 kB
11 - FFNs FeedForward Networks/106 - The MNIST dataset Vietnamese.vtt 20.4 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/219 - More on RNNs Hidden states embeddings English.vtt 20.4 kB
31 - Python intro Text and plots/260 - Subplot geometry English.vtt 20.4 kB
15 - Weight inits and investigations/144 - Theory Why and how to initialize weights Vietnamese.vtt 20.3 kB
31 - Python intro Text and plots/259 - Plotting dots and lines Vietnamese.vtt 20.3 kB
10 - Metaparameters activations optimizers/103 - Learning rate decay Vietnamese.vtt 20.2 kB
15 - Weight inits and investigations/148 - CodeChallenge Identically random weights Vietnamese.vtt 20.2 kB
9 - Regularization/80 - CodeChallenge Effects of minibatch size Vietnamese.vtt 20.2 kB
30 - Python intro Flow control/249 - Ifelse statements part 2 English.vtt 20.2 kB
16 - Autoencoders/153 - Denoising MNIST English.vtt 20.1 kB
15 - Weight inits and investigations/146 - Xavier and Kaiming initializations English.vtt 20.0 kB
5 - Math numpy PyTorch/23 - Mean and variance English.vtt 20.0 kB
17 - Running models on a GPU/158 - What is a GPU and why use it English.vtt 19.9 kB
7 - ANNs Artificial Neural Networks/42 - ANN math part 1 forward prop English.vtt 19.7 kB
18 - Convolution and transformations/164 - Convolution parameters stride padding Vietnamese.vtt 19.7 kB
9 - Regularization/76 - L1 regularization in practice Vietnamese.vtt 19.6 kB
10 - Metaparameters activations optimizers/99 - Optimizers RMSprop Adam English.vtt 19.6 kB
23 - Generative adversarial networks/210 - CNN GAN with Gaussians English.vtt 19.5 kB
6 - Gradient descent/31 - What about local minima Vietnamese.vtt 19.5 kB
11 - FFNs FeedForward Networks/111 - CodeChallenge MNIST and breadth vs depth Vietnamese.vtt 19.5 kB
12 - More on data/126 - Save the bestperforming model English.vtt 19.4 kB
20 - CNN milestone projects/190 - Project 1 My solution Vietnamese.vtt 19.4 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/215 - How RNNs work English.vtt 19.3 kB
25 - Ethics of deep learning/227 - Accountability and making ethical AI Vietnamese.vtt 19.3 kB
10 - Metaparameters activations optimizers/104 - How to pick the right metaparameters Vietnamese.vtt 19.3 kB
13 - Measuring model performance/129 - Accuracy precision recall F1 Vietnamese.vtt 19.2 kB
11 - FFNs FeedForward Networks/110 - Distributions of weights pre and postlearning English.vtt 19.2 kB
30 - Python intro Flow control/254 - Singleline loops list comprehension English.vtt 19.2 kB
7 - ANNs Artificial Neural Networks/53 - CodeChallenge more qwerties Vietnamese.vtt 19.2 kB
27 - Python intro Data types/237 - Dictionaries Vietnamese.vtt 19.2 kB
13 - Measuring model performance/132 - APRF example 2 MNIST Vietnamese.vtt 19.1 kB
6 - Gradient descent/34 - Gradient descent in 2D English.vtt 19.1 kB
11 - FFNs FeedForward Networks/114 - Shifted MNIST Vietnamese.vtt 19.1 kB
21 - Transfer learning/196 - CodeChallenge letters to numbers English.vtt 19.1 kB
3 - Concepts in deep learning/5 - What is an artificial neural network English.vtt 19.0 kB
30 - Python intro Flow control/248 - Ifelse statements English.vtt 19.0 kB
10 - Metaparameters activations optimizers/90 - Activation functions in PyTorch Vietnamese.vtt 19.0 kB
20 - CNN milestone projects/193 - Project 4 Psychometric functions in CNNs Vietnamese.vtt 19.0 kB
9 - Regularization/77 - Training in minibatches Vietnamese.vtt 19.0 kB
16 - Autoencoders/152 - What are autoencoders and what do they do Vietnamese.vtt 18.9 kB
14 - FFN milestone projects/137 - Project 1 My solution Vietnamese.vtt 18.9 kB
30 - Python intro Flow control/256 - Broadcasting in numpy English.vtt 18.8 kB
22 - Style transfer/203 - The Gram matrix feature activation covariance Vietnamese.vtt 18.5 kB
19 - Understand and design CNNs/179 - CodeChallenge How wide the FC Vietnamese.vtt 18.5 kB
6 - Gradient descent/30 - Overview of gradient descent English.vtt 18.5 kB
15 - Weight inits and investigations/142 - Explanation of weight matrix sizes Vietnamese.vtt 18.4 kB
5 - Math numpy PyTorch/24 - Random sampling and sampling variability Vietnamese.vtt 18.3 kB
5 - Math numpy PyTorch/18 - Matrix multiplication English.vtt 18.3 kB
30 - Python intro Flow control/251 - Enumerate and zip Vietnamese.vtt 18.2 kB
31 - Python intro Text and plots/262 - Seaborn Vietnamese.vtt 18.1 kB
10 - Metaparameters activations optimizers/96 - More practice with multioutput ANNs English.vtt 18.0 kB
27 - Python intro Data types/233 - Lists 1 of 2 English.vtt 17.9 kB
29 - Python intro Functions/242 - Python libraries pandas English.vtt 17.9 kB
18 - Convolution and transformations/169 - Pooling in PyTorch English.vtt 17.8 kB
29 - Python intro Functions/241 - Python libraries numpy English.vtt 17.7 kB
18 - Convolution and transformations/167 - Transpose convolution English.vtt 17.7 kB
6 - Gradient descent/33 - CodeChallenge unfortunate starting value Vietnamese.vtt 17.7 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/221 - The LSTM and GRU classes English.vtt 17.6 kB
11 - FFNs FeedForward Networks/115 - CodeChallenge The mystery of the missing 7 Vietnamese.vtt 17.6 kB
25 - Ethics of deep learning/225 - Some other possible ethical scenarios Vietnamese.vtt 17.5 kB
19 - Understand and design CNNs/187 - CodeChallenge Varying number of channels English.vtt 17.5 kB
10 - Metaparameters activations optimizers/84 - Data normalization English.vtt 17.5 kB
9 - Regularization/78 - Batch training in action Vietnamese.vtt 17.4 kB
19 - Understand and design CNNs/173 - The canonical CNN architecture Vietnamese.vtt 17.4 kB
29 - Python intro Functions/245 - Global and local variable scopes English.vtt 17.4 kB
5 - Math numpy PyTorch/26 - The ttest English.vtt 17.3 kB
7 - ANNs Artificial Neural Networks/41 - A geometric view of ANNs English.vtt 17.2 kB
3 - Concepts in deep learning/8 - Running experiments to understand DL English.vtt 17.2 kB
15 - Weight inits and investigations/149 - Freezing weights during learning English.vtt 17.1 kB
9 - Regularization/69 - Regularization Concept and methods English.vtt 17.0 kB
13 - Measuring model performance/131 - APRF example 1 wine quality English.vtt 17.0 kB
7 - ANNs Artificial Neural Networks/56 - Defining models using sequential vs class English.vtt 17.0 kB
25 - Ethics of deep learning/226 - Will deep learning take our jobs Vietnamese.vtt 16.9 kB
22 - Style transfer/204 - The style transfer algorithm Vietnamese.vtt 16.9 kB
9 - Regularization/75 - L2 regularization in practice English.vtt 16.8 kB
7 - ANNs Artificial Neural Networks/44 - ANN math part 3 backprop Vietnamese.vtt 16.7 kB
10 - Metaparameters activations optimizers/86 - Batch normalization English.vtt 16.7 kB
18 - Convolution and transformations/165 - The Conv2 class in PyTorch English.vtt 16.7 kB
24 - RNNs Recurrent Neural Networks and GRULSTM/214 - Leveraging sequences in deep learning English.vtt 16.7 kB
3 - Concepts in deep learning/6 - How models learn English.vtt 16.7 kB
12 - More on data/122 - Data noise augmentation with devsettest English.vtt 16.5 kB
17 - Running models on a GPU/159 - Implementation Vietnamese.vtt 16.5 kB
8 - Overfitting and crossvalidation/64 - Crossvalidation manual separation English.vtt 16.5 kB
18 - Convolution and transformations/170 - To pool or to stride Vietnamese.vtt 16.4 kB
15 - Weight inits and investigations/145 - CodeChallenge Weight variance inits English.vtt 16.4 kB
11 - FFNs FeedForward Networks/106 - The MNIST dataset English.vtt 16.4 kB
14 - FFN milestone projects/140 - Project 3 FFN for missing data interpolation Vietnamese.vtt 16.3 kB
8 - Overfitting and crossvalidation/61 - What is overfitting and is it as bad as they say English.vtt 16.3 kB
27 - Python intro Data types/234 - Lists 2 of 2 Vietnamese.vtt 16.3 kB
15 - Weight inits and investigations/144 - Theory Why and how to initialize weights English.vtt 16.3 kB
10 - Metaparameters activations optimizers/100 - Optimizers comparison Vietnamese.vtt 16.3 kB
5 - Math numpy PyTorch/22 - Minmax and argminargmax English.vtt 16.1 kB
9 - Regularization/80 - CodeChallenge Effects of minibatch size English.vtt 16.1 kB
18 - Convolution and transformations/164 - Convolution parameters stride padding English.vtt 16.0 kB
13 - Measuring model performance/129 - Accuracy precision recall F1 English.vtt 16.0 kB
28 - Python intro Indexing slicing/238 - Indexing English.vtt 16.0 kB
15 - Weight inits and investigations/148 - CodeChallenge Identically random weights English.vtt 15.9 kB
21 - Transfer learning/195 - Transfer learning MNIST FMNIST Vietnamese.vtt 15.9 kB
7 - ANNs Artificial Neural Networks/54 - Comparing the number of hidden units Vietnamese.vtt 15.9 kB
19 - Understand and design CNNs/185 - Dropout in CNNs Vietnamese.vtt 15.8 kB
10 - Metaparameters activations optimizers/103 - Learning rate decay English.vtt 15.8 kB
11 - FFNs FeedForward Networks/111 - CodeChallenge MNIST and breadth vs depth English.vtt 15.8 kB
28 - Python intro Indexing slicing/239 - Slicing English.vtt 15.8 kB
7 - ANNs Artificial Neural Networks/53 - CodeChallenge more qwerties English.vtt 15.8 kB
23 - Generative adversarial networks/209 - CodeChallenge Linear GAN with FMNIST Vietnamese.vtt 15.8 kB
13 - Measuring model performance/134 - Computation time Vietnamese.vtt 15.8 kB
25 - Ethics of deep learning/223 - Will AI save us or destroy us Vietnamese.vtt 15.7 kB
31 - Python intro Text and plots/259 - Plotting dots and lines English.vtt 15.6 kB
19 - Understand and design CNNs/181 - CodeChallenge AEs and occluded Gaussians Vietnamese.vtt 15.6 kB
8 - Overfitting and crossvalidation/67 - Splitting data into train devset test Vietnamese.vtt 15.6 kB
9 - Regularization/76 - L1 regularization in practice English.vtt 15.5 kB
10 - Metaparameters activations optimizers/85 - The importance of data normalization Vietnamese.vtt 15.4 kB
18 - Convolution and transformations/162 - Feature maps and convolution kernels Vietnamese.vtt 15.4 kB
20 - CNN milestone projects/190 - Project 1 My solution English.vtt 15.3 kB
15 - Weight inits and investigations/142 - Explanation of weight matrix sizes English.vtt 15.3 kB
6 - Gradient descent/31 - What about local minima English.vtt 15.3 kB
10 - Metaparameters activations optimizers/91 - Activation functions comparison Vietnamese.vtt 15.2 kB
13 - Measuring model performance/132 - APRF example 2 MNIST English.vtt 15.2 kB
7 - ANNs Artificial Neural Networks/43 - ANN math part 2 errors loss cost Vietnamese.vtt 15.2 kB
10 - Metaparameters activations optimizers/90 - Activation functions in PyTorch English.vtt 15.2 kB
5 - Math numpy PyTorch/13 - Spectral theories in mathematics Vietnamese.vtt 15.1 kB
20 - CNN milestone projects/193 - Project 4 Psychometric functions in CNNs English.vtt 15.0 kB
16 - Autoencoders/152 - What are autoencoders and what do they do English.vtt 15.0 kB
22 - Style transfer/203 - The Gram matrix feature activation covariance English.vtt 15.0 kB
10 - Metaparameters activations optimizers/104 - How to pick the right metaparameters English.vtt 15.0 kB
19 - Understand and design CNNs/179 - CodeChallenge How wide the FC English.vtt 15.0 kB
9 - Regularization/77 - Training in minibatches English.vtt 14.9 kB
14 - FFN milestone projects/137 - Project 1 My solution English.vtt 14.9 kB
27 - Python intro Data types/237 - Dictionaries English.vtt 14.9 kB
25 - Ethics of deep learning/227 - Accountability and making ethical AI English.vtt 14.9 kB
5 - Math numpy PyTorch/17 - OMG its the dot product Vietnamese.vtt 14.7 kB
11 - FFNs FeedForward Networks/114 - Shifted MNIST English.vtt 14.6 kB
5 - Math numpy PyTorch/29 - Derivatives product and chain rules Vietnamese.vtt 14.5 kB
5 - Math numpy PyTorch/24 - Random sampling and sampling variability English.vtt 14.5 kB
1 - Introduction/1 - How to learn from this course Vietnamese.vtt 14.3 kB
7 - ANNs Artificial Neural Networks/60 - Reflection Are DL models understandable yet Vietnamese.vtt 14.2 kB
30 - Python intro Flow control/251 - Enumerate and zip English.vtt 14.1 kB
6 - Gradient descent/33 - CodeChallenge unfortunate starting value English.vtt 14.1 kB
13 - Measuring model performance/133 - CodeChallenge MNIST with unequal groups Vietnamese.vtt 14.1 kB
19 - Understand and design CNNs/175 - CNN on shifted MNIST Vietnamese.vtt 14.1 kB
1 - Introduction/2 - Using Udemy like a pro Vietnamese.vtt 14.1 kB
7 - ANNs Artificial Neural Networks/50 - Linear solutions to linear problems Vietnamese.vtt 14.0 kB
19 - Understand and design CNNs/173 - The canonical CNN architecture English.vtt 14.0 kB
31 - Python intro Text and plots/262 - Seaborn English.vtt 14.0 kB
11 - FFNs FeedForward Networks/115 - CodeChallenge The mystery of the missing 7 English.vtt 13.9 kB
9 - Regularization/78 - Batch training in action English.vtt 13.9 kB
7 - ANNs Artificial Neural Networks/44 - ANN math part 3 backprop English.vtt 13.7 kB
13 - Measuring model performance/135 - Better performance in test than train Vietnamese.vtt 13.6 kB
25 - Ethics of deep learning/225 - Some other possible ethical scenarios English.vtt 13.6 kB
26 - Where to go from here/228 - How to learn topic X in deep learning Vietnamese.vtt 13.6 kB
27 - Python intro Data types/235 - Tuples Vietnamese.vtt 13.5 kB
8 - Overfitting and crossvalidation/68 - Crossvalidation on regression Vietnamese.vtt 13.5 kB
22 - Style transfer/204 - The style transfer algorithm English.vtt 13.4 kB
14 - FFN milestone projects/141 - Project 3 My solution Vietnamese.vtt 13.4 kB
5 - Math numpy PyTorch/25 - Reproducible randomness via seeding Vietnamese.vtt 13.4 kB
25 - Ethics of deep learning/226 - Will deep learning take our jobs English.vtt 13.2 kB
10 - Metaparameters activations optimizers/98 - SGD with momentum Vietnamese.vtt 13.2 kB
5 - Math numpy PyTorch/28 - Derivatives find minima Vietnamese.vtt 13.2 kB
23 - Generative adversarial networks/213 - CodeChallenge CNN GAN with CIFAR Vietnamese.vtt 13.2 kB
17 - Running models on a GPU/159 - Implementation English.vtt 13.1 kB
10 - Metaparameters activations optimizers/100 - Optimizers comparison English.vtt 13.0 kB
11 - FFNs FeedForward Networks/116 - Universal approximation theorem Vietnamese.vtt 13.0 kB
7 - ANNs Artificial Neural Networks/54 - Comparing the number of hidden units English.vtt 12.9 kB
18 - Convolution and transformations/170 - To pool or to stride English.vtt 12.9 kB
21 - Transfer learning/195 - Transfer learning MNIST FMNIST English.vtt 12.9 kB
31 - Python intro Text and plots/264 - Export plots in low and high resolution Vietnamese.vtt 12.9 kB
27 - Python intro Data types/234 - Lists 2 of 2 English.vtt 12.8 kB
11 - FFNs FeedForward Networks/113 - Scrambled MNIST Vietnamese.vtt 12.8 kB
14 - FFN milestone projects/140 - Project 3 FFN for missing data interpolation English.vtt 12.8 kB
25 - Ethics of deep learning/223 - Will AI save us or destroy us English.vtt 12.8 kB
19 - Understand and design CNNs/185 - Dropout in CNNs English.vtt 12.7 kB
12 - More on data/120 - What to do about unbalanced designs Vietnamese.vtt 12.7 kB
13 - Measuring model performance/134 - Computation time English.vtt 12.7 kB
10 - Metaparameters activations optimizers/92 - CodeChallenge Compare relu variants Vietnamese.vtt 12.5 kB
29 - Python intro Functions/243 - Getting help on functions Vietnamese.vtt 12.5 kB
18 - Convolution and transformations/162 - Feature maps and convolution kernels English.vtt 12.4 kB
7 - ANNs Artificial Neural Networks/43 - ANN math part 2 errors loss cost English.vtt 12.4 kB
10 - Metaparameters activations optimizers/87 - Batch normalization in practice Vietnamese.vtt 12.4 kB
19 - Understand and design CNNs/181 - CodeChallenge AEs and occluded Gaussians English.vtt 12.4 kB
5 - Math numpy PyTorch/17 - OMG its the dot product English.vtt 12.4 kB
23 - Generative adversarial networks/209 - CodeChallenge Linear GAN with FMNIST English.vtt 12.4 kB
10 - Metaparameters activations optimizers/85 - The importance of data normalization English.vtt 12.3 kB
5 - Math numpy PyTorch/20 - Logarithms Vietnamese.vtt 12.3 kB
8 - Overfitting and crossvalidation/67 - Splitting data into train devset test English.vtt 12.3 kB
20 - CNN milestone projects/189 - Project 1 Import and classify CIFAR10 Vietnamese.vtt 12.2 kB
5 - Math numpy PyTorch/13 - Spectral theories in mathematics English.vtt 12.1 kB
14 - FFN milestone projects/138 - Project 2 Predicting heart disease Vietnamese.vtt 12.1 kB
5 - Math numpy PyTorch/29 - Derivatives product and chain rules English.vtt 12.1 kB
10 - Metaparameters activations optimizers/91 - Activation functions comparison English.vtt 12.1 kB
14 - FFN milestone projects/136 - Project 1 A gratuitously complex adding machine Vietnamese.vtt 12.0 kB
29 - Python intro Functions/240 - Inputs and outputs Vietnamese.vtt 12.0 kB
5 - Math numpy PyTorch/14 - Terms and datatypes in math and computers Vietnamese.vtt 11.7 kB
13 - Measuring model performance/128 - Two perspectives of the world Vietnamese.vtt 11.7 kB
1 - Introduction/1 - How to learn from this course English.vtt 11.6 kB
22 - Style transfer/206 - CodeChallenge Style transfer with AlexNet Vietnamese.vtt 11.5 kB
18 - Convolution and transformations/166 - CodeChallenge Choose the parameters Vietnamese.vtt 11.5 kB
13 - Measuring model performance/133 - CodeChallenge MNIST with unequal groups English.vtt 11.4 kB
10 - Metaparameters activations optimizers/102 - CodeChallenge Adam with L2 regularization Vietnamese.vtt 11.3 kB
30 - Python intro Flow control/252 - Continue Vietnamese.vtt 11.3 kB
9 - Regularization/70 - train and eval modes Vietnamese.vtt 11.2 kB
5 - Math numpy PyTorch/16 - Vector and matrix transpose Vietnamese.vtt 11.2 kB
7 - ANNs Artificial Neural Networks/60 - Reflection Are DL models understandable yet English.vtt 11.2 kB
19 - Understand and design CNNs/186 - CodeChallenge How low can you go Vietnamese.vtt 11.1 kB
11 - FFNs FeedForward Networks/112 - CodeChallenge Optimizers and MNIST Vietnamese.vtt 11.0 kB
5 - Math numpy PyTorch/15 - Converting reality to numbers Vietnamese.vtt 11.0 kB
26 - Where to go from here/228 - How to learn topic X in deep learning English.vtt 11.0 kB
1 - Introduction/2 - Using Udemy like a pro English.vtt 10.9 kB
7 - ANNs Artificial Neural Networks/50 - Linear solutions to linear problems English.vtt 10.9 kB
5 - Math numpy PyTorch/28 - Derivatives find minima English.vtt 10.8 kB
19 - Understand and design CNNs/175 - CNN on shifted MNIST English.vtt 10.8 kB
13 - Measuring model performance/135 - Better performance in test than train English.vtt 10.8 kB
7 - ANNs Artificial Neural Networks/58 - CodeChallenge convert sequential to class Vietnamese.vtt 10.7 kB
9 - Regularization/79 - The importance of equal batch sizes Vietnamese.vtt 10.7 kB
10 - Metaparameters activations optimizers/101 - CodeChallenge Optimizers and something Vietnamese.vtt 10.6 kB
8 - Overfitting and crossvalidation/68 - Crossvalidation on regression English.vtt 10.6 kB
27 - Python intro Data types/235 - Tuples English.vtt 10.5 kB
14 - FFN milestone projects/141 - Project 3 My solution English.vtt 10.5 kB
13 - Measuring model performance/130 - APRF in code Vietnamese.vtt 10.5 kB
5 - Math numpy PyTorch/25 - Reproducible randomness via seeding English.vtt 10.5 kB
11 - FFNs FeedForward Networks/116 - Universal approximation theorem English.vtt 10.5 kB
6 - Gradient descent/38 - Vanishing and exploding gradients Vietnamese.vtt 10.5 kB
25 - Ethics of deep learning/224 - Example case studies Vietnamese.vtt 10.4 kB
23 - Generative adversarial networks/213 - CodeChallenge CNN GAN with CIFAR English.vtt 10.4 kB
12 - More on data/125 - Save and load trained models Vietnamese.vtt 10.3 kB
17 - Running models on a GPU/160 - CodeChallenge Run an experiment on the GPU Vietnamese.vtt 10.3 kB
23 - Generative adversarial networks/212 - CNN GAN with FMNIST Vietnamese.vtt 10.2 kB
5 - Math numpy PyTorch/20 - Logarithms English.vtt 10.2 kB
10 - Metaparameters activations optimizers/98 - SGD with momentum English.vtt 10.2 kB
9 - Regularization/73 - Dropout example 2 Vietnamese.vtt 10.2 kB
7 - ANNs Artificial Neural Networks/51 - Why multilayer linear models dont exist Vietnamese.vtt 10.2 kB
12 - More on data/124 - Getting data into colab Vietnamese.vtt 10.1 kB
31 - Python intro Text and plots/264 - Export plots in low and high resolution English.vtt 10.1 kB
10 - Metaparameters activations optimizers/92 - CodeChallenge Compare relu variants English.vtt 10.1 kB
11 - FFNs FeedForward Networks/113 - Scrambled MNIST English.vtt 10.0 kB
8 - Overfitting and crossvalidation/63 - Generalization Vietnamese.vtt 10.0 kB
12 - More on data/120 - What to do about unbalanced designs English.vtt 9.9 kB
2 - Download all course materials/3 - Downloading and using the code Vietnamese.vtt 9.9 kB
29 - Python intro Functions/243 - Getting help on functions English.vtt 9.9 kB
10 - Metaparameters activations optimizers/87 - Batch normalization in practice English.vtt 9.8 kB
23 - Generative adversarial networks/211 - CodeChallenge Gaussians with fewer layers Vietnamese.vtt 9.8 kB
14 - FFN milestone projects/138 - Project 2 Predicting heart disease English.vtt 9.8 kB
14 - FFN milestone projects/136 - Project 1 A gratuitously complex adding machine English.vtt 9.6 kB
20 - CNN milestone projects/189 - Project 1 Import and classify CIFAR10 English.vtt 9.5 kB
5 - Math numpy PyTorch/14 - Terms and datatypes in math and computers English.vtt 9.5 kB
29 - Python intro Functions/240 - Inputs and outputs English.vtt 9.4 kB
22 - Style transfer/206 - CodeChallenge Style transfer with AlexNet English.vtt 9.3 kB
21 - Transfer learning/197 - Famous CNN architectures Vietnamese.vtt 9.3 kB
10 - Metaparameters activations optimizers/102 - CodeChallenge Adam with L2 regularization English.vtt 9.3 kB
13 - Measuring model performance/128 - Two perspectives of the world English.vtt 9.1 kB
9 - Regularization/70 - train and eval modes English.vtt 9.1 kB
12 - More on data/127 - Where to find online datasets Vietnamese.vtt 9.1 kB
18 - Convolution and transformations/166 - CodeChallenge Choose the parameters English.vtt 9.1 kB
30 - Python intro Flow control/252 - Continue English.vtt 9.0 kB
5 - Math numpy PyTorch/16 - Vector and matrix transpose English.vtt 8.9 kB
11 - FFNs FeedForward Networks/112 - CodeChallenge Optimizers and MNIST English.vtt 8.9 kB
19 - Understand and design CNNs/186 - CodeChallenge How low can you go English.vtt 8.9 kB
17 - Running models on a GPU/160 - CodeChallenge Run an experiment on the GPU English.vtt 8.7 kB
7 - ANNs Artificial Neural Networks/58 - CodeChallenge convert sequential to class English.vtt 8.7 kB
5 - Math numpy PyTorch/15 - Converting reality to numbers English.vtt 8.5 kB
10 - Metaparameters activations optimizers/88 - CodeChallenge Batchnormalize the qwerties Vietnamese.vtt 8.4 kB
9 - Regularization/79 - The importance of equal batch sizes English.vtt 8.4 kB
6 - Gradient descent/35 - CodeChallenge 2D gradient ascent Vietnamese.vtt 8.4 kB
10 - Metaparameters activations optimizers/101 - CodeChallenge Optimizers and something English.vtt 8.4 kB
29 - Python intro Functions/246 - Copies and referents of variables Vietnamese.vtt 8.4 kB
2 - Download all course materials/3 - Downloading and using the code English.vtt 8.4 kB
13 - Measuring model performance/130 - APRF in code English.vtt 8.4 kB
11 - FFNs FeedForward Networks/108 - CodeChallenge Binarized MNIST images Vietnamese.vtt 8.3 kB
23 - Generative adversarial networks/212 - CNN GAN with FMNIST English.vtt 8.2 kB
25 - Ethics of deep learning/224 - Example case studies English.vtt 8.2 kB
7 - ANNs Artificial Neural Networks/51 - Why multilayer linear models dont exist English.vtt 8.2 kB
9 - Regularization/73 - Dropout example 2 English.vtt 8.2 kB
10 - Metaparameters activations optimizers/81 - What are metaparameters Vietnamese.vtt 8.1 kB
11 - FFNs FeedForward Networks/105 - What are fullyconnected and feedforward networks Vietnamese.vtt 8.1 kB
6 - Gradient descent/38 - Vanishing and exploding gradients English.vtt 8.0 kB
12 - More on data/125 - Save and load trained models English.vtt 8.0 kB
23 - Generative adversarial networks/211 - CodeChallenge Gaussians with fewer layers English.vtt 8.0 kB
8 - Overfitting and crossvalidation/63 - Generalization English.vtt 7.9 kB
12 - More on data/124 - Getting data into colab English.vtt 7.9 kB
21 - Transfer learning/197 - Famous CNN architectures English.vtt 7.8 kB
20 - CNN milestone projects/191 - Project 2 CIFARautoencoder Vietnamese.vtt 7.6 kB
12 - More on data/127 - Where to find online datasets English.vtt 7.3 kB
19 - Understand and design CNNs/188 - So many possibilities How to create a CNN Vietnamese.vtt 7.3 kB
22 - Style transfer/202 - What is style transfer and how does it work Vietnamese.vtt 7.2 kB
15 - Weight inits and investigations/151 - Use default inits or apply your own Vietnamese.vtt 7.1 kB
4 - About the Python tutorial/10 - Should you watch the Python tutorial Vietnamese.vtt 6.7 kB
6 - Gradient descent/35 - CodeChallenge 2D gradient ascent English.vtt 6.7 kB
10 - Metaparameters activations optimizers/88 - CodeChallenge Batchnormalize the qwerties English.vtt 6.7 kB
10 - Metaparameters activations optimizers/81 - What are metaparameters English.vtt 6.6 kB
11 - FFNs FeedForward Networks/108 - CodeChallenge Binarized MNIST images English.vtt 6.6 kB
29 - Python intro Functions/246 - Copies and referents of variables English.vtt 6.5 kB
20 - CNN milestone projects/191 - Project 2 CIFARautoencoder English.vtt 6.3 kB
11 - FFNs FeedForward Networks/105 - What are fullyconnected and feedforward networks English.vtt 6.3 kB
19 - Understand and design CNNs/188 - So many possibilities How to create a CNN English.vtt 5.8 kB
20 - CNN milestone projects/192 - Project 3 FMNIST Vietnamese.vtt 5.8 kB
15 - Weight inits and investigations/151 - Use default inits or apply your own English.vtt 5.7 kB
22 - Style transfer/202 - What is style transfer and how does it work English.vtt 5.7 kB
4 - About the Python tutorial/10 - Should you watch the Python tutorial English.vtt 5.5 kB
21 - Transfer learning/199 - CodeChallenge VGG16 Vietnamese.vtt 5.5 kB
27 - Python intro Data types/230 - How to learn from the Python tutorial Vietnamese.vtt 5.3 kB
20 - CNN milestone projects/192 - Project 3 FMNIST English.vtt 4.7 kB
21 - Transfer learning/199 - CodeChallenge VGG16 English.vtt 4.5 kB
27 - Python intro Data types/230 - How to learn from the Python tutorial English.vtt 4.4 kB
32 - Bonus section/265 - Bonus content.html 3.9 kB
5 - Math numpy PyTorch/12 - Introduction to this section Vietnamese.vtt 3.3 kB
6 - Gradient descent/39 - Tangent Notebook revision history Vietnamese.vtt 3.1 kB
2 - Download all course materials/4 - My policy on codesharing Vietnamese.vtt 2.8 kB
5 - Math numpy PyTorch/12 - Introduction to this section English.vtt 2.6 kB
6 - Gradient descent/39 - Tangent Notebook revision history English.vtt 2.5 kB
2 - Download all course materials/4 - My policy on codesharing English.vtt 2.3 kB
5 - Math numpy PyTorch/11 - PyTorch or TensorFlow.html 1.1 kB
7 - ANNs Artificial Neural Networks/59 - Diversity of ANN visual representations.html 517 Bytes
Readme.txt 145 Bytes
2 - Download all course materials/3 - Code on my github site.txt 61 Bytes

==查看完整文档列表==

上一个：HUNTA799C1.6 GB
下一个：TheLifeErotic.22.12.09.Jessica.A.Anal.Fun.2.XXX.1080p.HEVC.x265.PRT[XvX] 222.8 MB

24小时热门磁力链接

Andor [HDTV 720p][Cap.205] 8145次下载 Cap HDTV 720p
Маня и Груня.2024.WEB-DL 720p.Files-x 5109次下载 2024 WEB DL
Havoc.2025.1080p.NF.WEB-DL.DDP5.1.Atmos.H.264-EniaHD.mkv 5077次下载 WEB DL DDP5
The.Super.Cube.S01E09.1080p.iQ.WEB-DL.AAC2.0.H.264-VARYG.mkv 5040次下载 WEB DL Cube
Star.Wars.Andor.S02E05.I.Have.Friends.Everywhere.1080p.DS... 4944次下载 WEB DL Star
新桥恋人.电影港地址发布页 www.dygang.me 收藏不迷路 4365次下载 me www 发布页
Night at the Museum Battle of the Smithsonian 2009 2160p... 4161次下载 KiNGDOM WEB DL
www.UIndex.org - ... 4126次下载 www MeGusta HEVC
Palma.2.2024.WEB-DL.1080p.ExKinoRay.mkv 4000次下载 WEB DL 2.2024
Guns N' Roses - Greatest Hits Live Broadcast Collection... 3915次下载 Live Remastered Hits

本周热门磁力链接

Andor [HDTV 720p][Cap.205] 8145次下载 Cap HDTV 720p
(同人CG集) [白色絵の具 (無味ムスミ)] 友達の母が巨乳で金髪の淫乱美女でした.zip 6346次下载 zip 巨乳 CG
You.S05E02.720p.HEVC.x265-MeGusta[EZTVx.to].mkv 6221次下载 S05E02 HEVC 720p
up-mod-minecraft-play-with-friends-v1-21-80-28-... 6023次下载 982108028 mod play
the.last.of.us.s02e02.1080p.web.h264-successful... 5335次下载 web last h264
异世降临.6v电影地址发布页 www.6v123.net 收藏不迷路 5220次下载 www 发布页 6v123
Opasnaya.blizost.S01.2025.WEB-DL.1080p 5127次下载 WEB DL S01
Маня и Груня.2024.WEB-DL 720p.Files-x 5109次下载 2024 WEB DL
Andor.S02E02.Sagrona.Teema.1080p.HEVC.x265-MeGu... 5100次下载 HEVC Andor mkv
Havoc.2025.1080p.NF.WEB-DL.DDP5.1.Atmos.H.264-E... 5077次下载 WEB DL DDP5

种子标签

种子评价

优质的种子 (0) 假种子 (0) 有密码 (0) 低质量 (0) 有病毒 (0) 无法下载 (0)
欢迎对种子质量进行评价。

人气女优

北川ゆい Akira COCOLO Saiko あいだももあさのくるみあまいれもんいしかわ愛里いとうしいなうさみ恭香うちだまひろかぐやひめかとりこのみかないかほくすのき琴美クミコグレースくらもとまい（葉月ありさ）さとみ中村あみしいな純菜しのざきさとみ（三沢亜也）牧本千幸（つかもと友希）眞木ありさデヴィテラパトリックドミニカともさかまいともさか愛なごみもえひなこ

分享BT种子/磁力链接

亲，你知道吗？下载的人越多速度越快，赶快把本页面分享给好友一起下载吧^_^

磁力管家