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- 【影视】 [GigaCourse.Com] Udemy - TensorFlow Developer Certificate in 2021 Zero to Mastery
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收录时间:2022-02-02
文档个数:820
文档大小:36.6 GB
最近下载:2025-05-15
人气:699
磁力链接
10 NLP Fundamentals in TensorFlow/016 Visualising our model's learned word embeddings with TensorFlow's projector tool.mp4 296.9 MB
12 Time Series fundamentals in TensorFlow + Milestone Project 3_ BitPredict/023 Writing a preprocessing function to turn time series data into windows & labels.mp4 262.6 MB
12 Time Series fundamentals in TensorFlow + Milestone Project 3_ BitPredict/047 Model 7_ Putting together the pieces of the puzzle of the N-BEATS model.mp4 248.9 MB
11 Milestone Project 2_ SkimLit/006 Writing a preprocessing function to structure our data for modelling.mp4 228.6 MB
12 Time Series fundamentals in TensorFlow + Milestone Project 3_ BitPredict/041 Model 7_ Replicating the N-BEATS basic block with TensorFlow layer subclassing.mp4 226.8 MB
10 NLP Fundamentals in TensorFlow/015 Model 1_ Building, fitting and evaluating our first deep model on text data.mp4 217.9 MB
10 NLP Fundamentals in TensorFlow/009 Setting up a TensorFlow TextVectorization layer to convert text to numbers.mp4 209.8 MB
07 Transfer Learning in TensorFlow Part 2_ Fine tuning/018 Preparing Model 3 (our first fine-tuned model).mp4 207.9 MB
11 Milestone Project 2_ SkimLit/017 Creating a character-level tokeniser with TensorFlow's TextVectorization layer.mp4 206.9 MB
03 Neural network regression with TensorFlow/011 Evaluating a TensorFlow model part 3 (getting a model summary).mp4 202.4 MB
05 Computer Vision and Convolutional Neural Networks in TensorFlow/015 Breaking our CNN model down part 5_ Looking inside a Conv2D layer.mp4 195.0 MB
10 NLP Fundamentals in TensorFlow/021 Discussing the intuition behind Conv1D neural networks for text and sequences.mp4 193.3 MB
12 Time Series fundamentals in TensorFlow + Milestone Project 3_ BitPredict/042 Model 7_ Testing our N-BEATS block implementation with dummy data inputs.mp4 191.9 MB
12 Time Series fundamentals in TensorFlow + Milestone Project 3_ BitPredict/051 Model 8_ Making and evaluating predictions with our ensemble model.mp4 191.0 MB
03 Neural network regression with TensorFlow/005 The major steps in modelling with TensorFlow.mp4 190.7 MB
11 Milestone Project 2_ SkimLit/021 Model 4_ Building a multi-input model (hybrid token + character embeddings).mp4 190.4 MB
12 Time Series fundamentals in TensorFlow + Milestone Project 3_ BitPredict/050 Model 8_ Building, compiling and fitting an ensemble of models.mp4 188.8 MB
07 Transfer Learning in TensorFlow Part 2_ Fine tuning/003 Downloading and turning our images into a TensorFlow BatchDataset.mp4 181.7 MB
08 Transfer Learning with TensorFlow Part 3_ Scaling Up/018 Making predictions on our test images and evaluating them.mp4 180.0 MB
11 Milestone Project 2_ SkimLit/014 Model 1_ Building, fitting and evaluating a Conv1D with token embeddings.mp4 176.5 MB
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- 【影视】 [FreeCourseSite.com] Udemy - TensorFlow Developer Certificate in 2022 Zero to Mastery
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10 - NLP Fundamentals in TensorFlow/016 Visualising our model's learned word embeddings with TensorFlow's projector tool.mp4 300.8 MB
10 - NLP Fundamentals in TensorFlow/015 Model 1 Building, fitting and evaluating our first deep model on text data.mp4 215.3 MB
10 - NLP Fundamentals in TensorFlow/009 Setting up a TensorFlow TextVectorization layer to convert text to numbers.mp4 209.5 MB
07 - Transfer Learning in TensorFlow Part 2 Fine tuning/019 Preparing Model 3 (our first fine-tuned model).mp4 203.4 MB
03 - Neural network regression with TensorFlow/012 Evaluating a TensorFlow model part 3 (getting a model summary).mp4 201.9 MB
11 - Milestone Project 2 SkimLit/017 Creating a character-level tokeniser with TensorFlow's TextVectorization layer.mp4 200.8 MB
05 - Computer Vision and Convolutional Neural Networks in TensorFlow/015 Breaking our CNN model down part 5 Looking inside a Conv2D layer.mp4 195.8 MB
10 - NLP Fundamentals in TensorFlow/021 Discussing the intuition behind Conv1D neural networks for text and sequences.mp4 189.8 MB
11 - Milestone Project 2 SkimLit/021 Model 4 Building a multi-input model (hybrid token + character embeddings).mp4 189.7 MB
03 - Neural network regression with TensorFlow/006 The major steps in modelling with TensorFlow.mp4 188.7 MB
12 - Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/050 Model 8 Building, compiling and fitting an ensemble of models.mp4 184.2 MB
07 - Transfer Learning in TensorFlow Part 2 Fine tuning/003 Downloading and turning our images into a TensorFlow BatchDataset.mp4 180.6 MB
08 - Transfer Learning with TensorFlow Part 3 Scaling Up/018 Making predictions on our test images and evaluating them.mp4 176.8 MB
11 - Milestone Project 2 SkimLit/014 Model 1 Building, fitting and evaluating a Conv1D with token embeddings.mp4 174.1 MB
10 - NLP Fundamentals in TensorFlow/019 Model 3 Building, fitting and evaluating a GRU-cell powered RNN.mp4 174.0 MB
10 - NLP Fundamentals in TensorFlow/027 Fixing our data leakage issue with model 7 and retraining it.mp4 173.5 MB
10 - NLP Fundamentals in TensorFlow/020 Model 4 Building, fitting and evaluating a bidirectional RNN model.mp4 170.7 MB
10 - NLP Fundamentals in TensorFlow/018 Model 2 Building, fitting and evaluating our first TensorFlow RNN model (LSTM).mp4 170.3 MB
04 - Neural network classification in TensorFlow/009 Creating a function to view our model's not so good predictions.mp4 167.0 MB
10 - NLP Fundamentals in TensorFlow/006 Becoming one with the data and visualising a text dataset.mp4 165.9 MB
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- 【影视】 [ TutGator.com ] Linkedin - TensorFlow - Working with Images
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收录时间:2022-02-12
文档个数:36
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~Get Your Files Here !/3. Transfer Learning/011. Transfer learning with TensorFlow Hub.mp4 48.6 MB
~Get Your Files Here !/4. Monitoring the Training Process/016. Using TensorBoard.mp4 42.3 MB
~Get Your Files Here !/4. Monitoring the Training Process/014. Using ModelCheckpoint.mp4 39.0 MB
~Get Your Files Here !/2. Neural Networks and Images/004. Review of neural networks.mp4 36.5 MB
~Get Your Files Here !/2. Neural Networks and Images/007. Solution Experiment with hyperparameters.mp4 32.3 MB
~Get Your Files Here !/2. Neural Networks and Images/005. Working with color images and neural networks.mp4 29.6 MB
~Get Your Files Here !/3. Transfer Learning/012. TensorFlow Hub for CIFAR-10.mp4 24.2 MB
~Get Your Files Here !/1. Introduction/003. What is TensorFlow.mp4 23.1 MB
~Get Your Files Here !/3. Transfer Learning/009. TensorFlow Hub.mp4 22.1 MB
~Get Your Files Here !/2. Neural Networks and Images/006. Challenge Experiment with hyperparameters.mp4 16.8 MB
~Get Your Files Here !/3. Transfer Learning/010. What is transfer learning.mp4 14.8 MB
~Get Your Files Here !/3. Transfer Learning/008. Why the poor performance with neural networks.mp4 11.0 MB
~Get Your Files Here !/4. Monitoring the Training Process/013. Monitoring the training process.mp4 7.8 MB
~Get Your Files Here !/4. Monitoring the Training Process/015. Working with EarlyStopping.mp4 7.5 MB
~Get Your Files Here !/1. Introduction/001. Work with gray and color images using transfer learning and fine-tuning.mp4 5.9 MB
~Get Your Files Here !/1. Introduction/002. What you should know.mp4 4.0 MB
~Get Your Files Here !/5. Conclusion/017. Next steps.mp4 3.4 MB
~Get Your Files Here !/3. Transfer Learning/011. Transfer learning with TensorFlow Hub.en.srt 9.2 kB
~Get Your Files Here !/4. Monitoring the Training Process/016. Using TensorBoard.en.srt 8.2 kB
~Get Your Files Here !/2. Neural Networks and Images/004. Review of neural networks.en.srt 7.0 kB
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- 【影视】 desire-course.-net-udemy-tensorflow-2.0-deep-learning-and-artificial-intelligence_202008
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18. Setting up your Environment/2. Windows-Focused Environment Setup 2018.mp4 203.4 MB
18. Setting up your Environment/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 175.4 MB
18. Setting up your Environment/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 174.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4 150.1 MB
13. Advanced Tensorflow Usage/2. Tensorflow Serving pt 2.mp4 130.5 MB
20. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).mp4 128.6 MB
20. Effective Learning Strategies for Machine Learning/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 122.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 108.2 MB
11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4 102.5 MB
4. Feedforward Artificial Neural Networks/4. Activation Functions.mp4 96.7 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.mp4 96.5 MB
5. Convolutional Neural Networks/5. CNN Architecture.mp4 95.4 MB
2. Google Colab/3. Uploading your own data to Google Colab.mp4 93.4 MB
20. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).mp4 92.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4 91.9 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 91.5 MB
10. GANs (Generative Adversarial Networks)/1. GAN Theory.mp4 90.7 MB
5. Convolutional Neural Networks/11. Improving CIFAR-10 Results.mp4 90.6 MB
5. Convolutional Neural Networks/6. CNN Code Preparation.mp4 90.5 MB
4. Feedforward Artificial Neural Networks/9. ANN for Regression.mp4 88.0 MB
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- 【影视】 [FreeCoursesOnline.Me] FrontendMasters - A Practical Guide to Deep Learning with TensorFlow 2.0 and Keras
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收录时间:2021-03-29
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A Practical Guide to Deep Learning with TensorFlow 2.0 and K (28).mp4 196.5 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (27).mp4 188.6 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (2).mp4 188.1 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (20).mp4 185.1 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (25).mp4 179.8 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (3).mp4 179.5 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (22).mp4 177.9 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (26).mp4 177.8 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (21).mp4 176.5 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (7).mp4 176.3 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (16).mp4 173.7 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (18).mp4 173.7 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (5).mp4 171.0 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (1).mp4 170.6 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (10).mp4 167.2 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (11).mp4 165.6 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (9).mp4 164.8 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (6).mp4 161.7 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (15).mp4 147.8 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (17).mp4 140.9 MB
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- 【影视】 [DesireCourse.Net] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API
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16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4 92.5 MB
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- 【影视】 [Udemy] TensorFlow Developer Certificate in 2021 Zero to Mastery (2021) [En]
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7. Transfer Learning in TensorFlow Part 2 Fine tuning/18. Preparing Model 3 (our first fine-tuned model).mp4 207.9 MB
3. Neural network regression with TensorFlow/11. Evaluating a TensorFlow model part 3 (getting a model summary).mp4 202.2 MB
5. Computer Vision and Convolutional Neural Networks in TensorFlow/15. Breaking our CNN model down part 5 Looking inside a Conv2D layer.mp4 195.1 MB
3. Neural network regression with TensorFlow/5. The major steps in modelling with TensorFlow.mp4 190.6 MB
7. Transfer Learning in TensorFlow Part 2 Fine tuning/3. Downloading and turning our images into a TensorFlow BatchDataset.mp4 182.0 MB
8. Transfer Learning with TensorFlow Part 3 Scaling Up/18. Making predictions on our test images and evaluating them.mp4 180.0 MB
4. Neural network classification in TensorFlow/9. Creating a function to view our model's not so good predictions.mp4 168.3 MB
7. Transfer Learning in TensorFlow Part 2 Fine tuning/14. Building Model 2 (with a data augmentation layer and 10% of training data).mp4 167.5 MB
5. Computer Vision and Convolutional Neural Networks in TensorFlow/20. Breaking our CNN model down part 10 Visualizing our augmented data.mp4 165.3 MB
8. Transfer Learning with TensorFlow Part 3 Scaling Up/14. Creating a confusion matrix for our model's 101 different classes.mp4 164.2 MB
4. Neural network classification in TensorFlow/18. Using callbacks to find a model's ideal learning rate.mp4 163.5 MB
3. Neural network regression with TensorFlow/25. Putting together what we've learned part 3 (improving our regression model).mp4 162.6 MB
5. Computer Vision and Convolutional Neural Networks in TensorFlow/7. Building an end to end CNN Model.mp4 162.6 MB
7. Transfer Learning in TensorFlow Part 2 Fine tuning/13. Building Model 1 (with a data augmentation layer and 1% of training data).mp4 160.4 MB
7. Transfer Learning in TensorFlow Part 2 Fine tuning/8. Getting a feature vector from our trained model.mp4 154.8 MB
4. Neural network classification in TensorFlow/15. Non-linearity part 5 Replicating non-linear activation functions from scratch.mp4 153.7 MB
6. Transfer Learning in TensorFlow Part 1 Feature extraction/10. Comparing Our Model's Results.mp4 150.9 MB
3. Neural network regression with TensorFlow/23. Putting together what we've learned part 1 (preparing a dataset).mp4 150.5 MB
4. Neural network classification in TensorFlow/26. Multi-class classification part 3 Building a multi-class classification model.mp4 149.7 MB
5. Computer Vision and Convolutional Neural Networks in TensorFlow/27. Multi-class CNN's part 1 Becoming one with the data.mp4 147.0 MB
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- 【影视】 Packt - Tensorflow Deep Learning Solutions for Images
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tensorflowdeeplearningsolutionsforimages_video.docx 18.1 kB
video1_1.mp4 7.7 MB
video1_2.mp4 14.1 MB
video1_3.mp4 8.1 MB
video1_4.mp4 5.7 MB
video1_5.mp4 11.3 MB
video2_1.mp4 8.8 MB
video2_2.mp4 9.7 MB
video2_3.mp4 8.9 MB
video2_4.mp4 6.7 MB
video3_1.mp4 6.4 MB
video3_2.mp4 4.4 MB
video3_3.mp4 11.2 MB
video3_4.mp4 6.9 MB
video3_5.mp4 7.8 MB
video3_6.mp4 9.7 MB
video3_7.mp4 5.1 MB
video3_8.mp4 15.6 MB
video4_1.mp4 7.5 MB
video4_2.mp4 8.0 MB
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收录时间:2024-11-26
文档个数:245
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lesson154.mp4 151.4 MB
lesson40.mp4 148.6 MB
lesson139.mp4 131.9 MB
lesson105.mp4 131.6 MB
lesson144.mp4 130.6 MB
lesson75.mp4 126.4 MB
lesson66.mp4 125.5 MB
lesson143.mp4 124.1 MB
lesson54.mp4 123.0 MB
lesson175.mp4 119.3 MB
lesson179.mp4 118.2 MB
lesson34.mp4 118.1 MB
lesson149.mp4 110.0 MB
lesson73.mp4 109.2 MB
lesson150.mp4 109.1 MB
lesson110.mp4 108.6 MB
lesson142.mp4 108.1 MB
lesson117.mp4 107.9 MB
lesson72.mp4 105.7 MB
lesson97.mp4 102.0 MB
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- 【影视】 [FreeCoursesOnline.Me] [Packt] Interactive Chatbots with TensorFlow [FCO]
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6 - Contextual Generative Chatbots/37 - Building a Contextually Aware System.mp4 39.7 MB
1 - NLP Practices for Chatbot Development/02 - Tokenization.mp4 37.4 MB
5 - Making Your Chatbot Attentive/33 - Training and Evaluating the Model.mp4 34.8 MB
3 - Integrating Neural Networks/15 - Understanding Overfitting and Regularization.mp4 29.7 MB
6 - Contextual Generative Chatbots/38 - Conclusion.mp4 29.1 MB
3 - Integrating Neural Networks/18 - Applying LSTM to Named Entity Recognition.mp4 26.7 MB
4 - Generative Chatbots - Chatbots of the future/24 - Building the Encoder.mp4 23.9 MB
3 - Integrating Neural Networks/19 - Text Classification Using LSTM.mp4 22.2 MB
1 - NLP Practices for Chatbot Development/01 - The Course Overview.mp4 19.7 MB
3 - Integrating Neural Networks/13 - Implementing Linear Models.mp4 16.6 MB
4 - Generative Chatbots - Chatbots of the future/23 - Preprocessing the Data.mp4 15.5 MB
4 - Generative Chatbots - Chatbots of the future/22 - Preparing Data for the Model.mp4 14.7 MB
4 - Generative Chatbots - Chatbots of the future/26 - Training and Evaluating the Model.mp4 12.7 MB
3 - Integrating Neural Networks/16 - Training Word2vec Models.mp4 12.1 MB
1 - NLP Practices for Chatbot Development/05 - Vectorization.mp4 9.8 MB
5 - Making Your Chatbot Attentive/32 - Adding Attention to Our seq2seq Model.mp4 9.6 MB
4 - Generative Chatbots - Chatbots of the future/27 - Deploying the Chatbot.mp4 9.0 MB
1 - NLP Practices for Chatbot Development/03 - Stemming.mp4 8.6 MB
1 - NLP Practices for Chatbot Development/06 - Word Embedding.mp4 7.3 MB
2 - Building a Retrieval-Based Chatbot/12 - Building Your First Functional Chatbot.mp4 6.9 MB
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21 Gerac227o automatica de caracteres/102 Construc227o da GAN - MNIST IV.mp4 152.5 MB
12 Classificac227o de digitos escritos a m227o/073 Redes convolucionais com estimators V.mp4 148.6 MB
09 Redes neurais para classificac227o e regress227o com TensorFlow/051 Classificac227o multiclasse - base iris II.mp4 144.3 MB
06 Classificac227o/031 Regress227o logistica com estimators I.mp4 144.0 MB
15 Serie temporal - precos da bolsa de valores/081 Base de dados para redes recorrentes II.mp4 142.9 MB
21 Gerac227o automatica de caracteres/101 Construc227o da GAN - MNIST III.mp4 138.2 MB
15 Serie temporal - precos da bolsa de valores/080 Base de dados para redes recorrentes I.mp4 127.0 MB
09 Redes neurais para classificac227o e regress227o com TensorFlow/050 Classificac227o multiclasse - base iris I.mp4 121.6 MB
22 Ap234ndice A - Basico sobre aprendizagem de maquina/107 Introduc227o a avaliac227o de algoritmos.mp4 118.3 MB
15 Serie temporal - precos da bolsa de valores/083 Redes neurais recorrentes II.mp4 117.2 MB
08 Teoria resumida sobre redes neurais artificiais/043 TensorFlow playground.mp4 113.6 MB
21 Gerac227o automatica de caracteres/100 Construc227o da GAN - MNIST II.mp4 113.2 MB
09 Redes neurais para classificac227o e regress227o com TensorFlow/055 Classificac227o de digitos manuscritos III.mp4 112.7 MB
12 Classificac227o de digitos escritos a m227o/072 Redes convolucionais com estimators IV.mp4 112.6 MB
18 Reduc227o de dimensionalidade/094 Stacked autoencoder - MNIST III.mp4 111.7 MB
09 Redes neurais para classificac227o e regress227o com TensorFlow/048 Classificac227o binaria - XOR II.mp4 111.7 MB
05 Regress227o linear/025 Regress227o linear simples com estimators II.mp4 110.6 MB
05 Regress227o linear/027 Regress227o linear multipla com estimators II.mp4 109.3 MB
21 Gerac227o automatica de caracteres/099 Construc227o da GAN - MNIST I.mp4 107.4 MB
22 Ap234ndice A - Basico sobre aprendizagem de maquina/108 Introduc227o a redes neurais artificiais I.mp4 106.7 MB
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- 【影视】 [GigaCourse.Com] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API
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01 - Introduction/001 Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit.mp4 153.4 MB
02 - TensorFlow 2.0 Basics/001 From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
17 - Annex 3 - Recurrent Neural Networks Theory/005 LSTM Practical Intuition.mp4 112.7 MB
17 - Annex 3 - Recurrent Neural Networks Theory/004 LSTMs.mp4 93.2 MB
16 - Annex 2 - Convolutional Neural Networks Theory/005 Step 2 - Max Pooling.mp4 91.7 MB
17 - Annex 3 - Recurrent Neural Networks Theory/003 Vanishing Gradient.mp4 90.4 MB
16 - Annex 2 - Convolutional Neural Networks Theory/002 What are Convolutional Neural Networks.mp4 74.5 MB
16 - Annex 2 - Convolutional Neural Networks Theory/003 Step 1 - Convolution.mp4 68.8 MB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/005 Dataset preprocessing pipeline.mp4 62.7 MB
16 - Annex 2 - Convolutional Neural Networks Theory/007 Step 4 - Full Connection.mp4 61.4 MB
17 - Annex 3 - Recurrent Neural Networks Theory/002 What are Recurrent Neural Networks.mp4 60.3 MB
04 - Convolutional Neural Networks/002 Building the Convolutional Neural Network.mp4 59.3 MB
07 - Deep Reinforcement Learning Theory/009 Action Selection Policies.mp4 57.0 MB
16 - Annex 2 - Convolutional Neural Networks Theory/009 Softmax & Cross-Entropy.mp4 53.9 MB
07 - Deep Reinforcement Learning Theory/002 The Bellman Equation.mp4 50.6 MB
06 - Transfer Learning and Fine Tuning/001 What is Transfer Learning.mp4 48.7 MB
06 - Transfer Learning and Fine Tuning/002 Project Setup.mp4 46.6 MB
15 - Annex 1 - Artificial Neural Networks Theory/002 The Neuron.mp4 45.8 MB
15 - Annex 1 - Artificial Neural Networks Theory/005 How do Neural Networks Learn.mp4 45.4 MB
07 - Deep Reinforcement Learning Theory/003 Markov Decision Process (MDP).mp4 44.4 MB
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3. Natural language processing/6. Q&A and information retrieval 2.mp4 162.5 MB
2. Computer vision/5. Image classification 4.mp4 114.3 MB
2. Computer vision/7. Object detection 1.mp4 109.9 MB
2. Computer vision/2. Image classification 1.mp4 107.9 MB
2. Computer vision/14. Image extension using GAN 2.mp4 99.0 MB
3. Natural language processing/8. Q&A and information retrieval 4.mp4 96.5 MB
2. Computer vision/17. Action recognition 3.mp4 95.5 MB
3. Natural language processing/9. Q&A and information retrieval 5.mp4 92.7 MB
2. Computer vision/9. Object detection 3.mp4 90.5 MB
2. Computer vision/6. Image classification 5.mp4 89.9 MB
3. Natural language processing/3. Text classification 2.mp4 87.7 MB
2. Computer vision/15. Action recognition 1.mp4 85.5 MB
3. Natural language processing/7. Q&A and information retrieval 3.mp4 84.3 MB
1. Introduction/1. Course content.mp4 83.2 MB
2. Computer vision/18. Action recognition 4.mp4 79.1 MB
2. Computer vision/3. Image classification 2.mp4 71.6 MB
2. Computer vision/4. Image classification 3.mp4 68.4 MB
3. Natural language processing/10. Audio classification 1.mp4 68.2 MB
4. Extra content 1 Artificial neural networks/8. Bias, error, stochastic gradient descent, and more parameters.mp4 66.5 MB
2. Computer vision/11. Style transfer 2.mp4 65.5 MB
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[TutsNode.com] - Neural Networks with Tensorflow/2. In Progress/3. Neural Style Transfer with VGG19 - 3.mp4 128.0 MB
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[TutsNode.com] - Neural Networks with Tensorflow/1. Lessons/21. CNN and Cifar10 - 3.mp4 84.8 MB
[TutsNode.com] - Neural Networks with Tensorflow/1. Lessons/18. Convolutional Neural Networks - 6.mp4 84.2 MB
[TutsNode.com] - Neural Networks with Tensorflow/1. Lessons/33. Recurrent Neural Networks - 8.mp4 82.7 MB
[TutsNode.com] - Neural Networks with Tensorflow/1. Lessons/12. Handwriting Recognition with MNIST.mp4 82.2 MB
[TutsNode.com] - Neural Networks with Tensorflow/1. Lessons/19. CNN and Cifar10 - 1.mp4 75.0 MB
[TutsNode.com] - Neural Networks with Tensorflow/1. Lessons/23. CNN and Cifar10 - 5.mp4 73.2 MB
[TutsNode.com] - Neural Networks with Tensorflow/1. Lessons/22. CNN and Cifar10 - 4.mp4 72.2 MB
[TutsNode.com] - Neural Networks with Tensorflow/2. In Progress/2. Neural Style Transfer with VGG19 - 2.mp4 70.0 MB
[TutsNode.com] - Neural Networks with Tensorflow/1. Lessons/32. Recurrent Neural Networks - 7.mp4 68.0 MB
[TutsNode.com] - Neural Networks with Tensorflow/1. Lessons/31. Recurrent Neural Networks - 6.mp4 66.3 MB
[TutsNode.com] - Neural Networks with Tensorflow/1. Lessons/28. Recurrent Neural Networks - 3.mp4 64.7 MB
[TutsNode.com] - Neural Networks with Tensorflow/1. Lessons/24. Tactics to Improve the Model.mp4 60.3 MB
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01.Welcome! Course introduction/0101.Meet your instructors and why you should study machine learning.mp4 88.9 MB
06.Going deeper Introduction to deep neural networks/0603.Understanding deep nets in depth.mp4 61.0 MB
02.Introduction to neural networks/0212.N-parameter gradient descent.mp4 60.4 MB
02.Introduction to neural networks/0211.One parameter gradient descent.mp4 59.1 MB
06.Going deeper Introduction to deep neural networks/0607.Backpropagation.mp4 55.3 MB
03.Setting up the working environment/0306.Installing TensorFlow 2.mp4 53.7 MB
02.Introduction to neural networks/0201.Introduction to neural networks.mp4 48.0 MB
12.Business case/1204.Preprocessing the data.mp4 46.7 MB
02.Introduction to neural networks/0206.The linear model. Multiple inputs and multiple outputs.mp4 44.3 MB
05.TensorFlow - An introduction/0501.TensorFlow outline.mp4 44.0 MB
02.Introduction to neural networks/0203.Types of machine learning.mp4 42.8 MB
10.Preprocessing/1003.Standardization.mp4 42.3 MB
13.Conclusion/1305.An overview of non-NN approaches.mp4 42.1 MB
01.Welcome! Course introduction/0102.What does the course cover.mp4 41.0 MB
13.Conclusion/1301.See how much you have learned.mp4 40.8 MB
06.Going deeper Introduction to deep neural networks/0604.Why do we need non-linearities.mp4 39.8 MB
06.Going deeper Introduction to deep neural networks/0605.Activation functions.mp4 39.8 MB
05.TensorFlow - An introduction/0502.TensorFlow 2 intro.mp4 39.7 MB
07.Overfitting/0703.Training and validation.mp4 39.3 MB
09.Gradient descent and learning rates/0904.Learning rate schedules.mp4 38.9 MB
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14. Appendix Linear Algebra Fundamentals/11. Why is Linear Algebra Useful.mp4 151.3 MB
1. Welcome! Course introduction/1. Meet your instructors and why you should study machine learning.mp4 110.9 MB
14. Appendix Linear Algebra Fundamentals/3. Linear Algebra and Geometry.mp4 52.2 MB
14. Appendix Linear Algebra Fundamentals/10. Dot Product of Matrices.mp4 51.8 MB
2. Introduction to neural networks/24. N-parameter gradient descent.mp4 41.4 MB
2. Introduction to neural networks/12. The linear model. Multiple inputs and multiple outputs.mp4 40.1 MB
14. Appendix Linear Algebra Fundamentals/8. Transpose of a Matrix.mp4 39.9 MB
13. Business case/4. Preprocessing the data.mp4 36.0 MB
14. Appendix Linear Algebra Fundamentals/2. Scalars and Vectors.mp4 35.5 MB
14. Appendix Linear Algebra Fundamentals/1. What is a Matrix.mp4 35.2 MB
14. Appendix Linear Algebra Fundamentals/6. Addition and Subtraction of Matrices.mp4 34.2 MB
13. Business case/6. Create a class for batching.mp4 29.0 MB
14. Appendix Linear Algebra Fundamentals/4. Scalars, Vectors and Matrices in Python.mp4 28.0 MB
14. Appendix Linear Algebra Fundamentals/9. Dot Product of Vectors.mp4 25.2 MB
13. Business case/1. Exploring the dataset and identifying predictors.mp4 24.4 MB
14. Appendix Linear Algebra Fundamentals/5. Tensors.mp4 23.6 MB
12. The MNIST example/9. Discuss the results and test.mp4 23.0 MB
4. Minimal example - your first machine learning algorithm/4. Minimal example - part 4.mp4 21.8 MB
13. Business case/7. Outlining the model.mp4 20.4 MB
12. The MNIST example/4. Outlining the model.mp4 19.3 MB
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3.Natural Language Processing and Recurrent Neural Networks/10.Embeddings.mp4 374.1 MB
6.Miscellaneous Topics and Course Summary/25.TensorFlow Eager.mp4 327.1 MB
1.TensorFlow Setup and Fundamental Concepts/03.TensorFlow Basics Part 1 - Tensors and Variables.mp4 118.8 MB
6.Miscellaneous Topics and Course Summary/23.TPUs.mp4 109.9 MB
2.Computer Vision/06.Convolutional Neural Networks.mp4 106.2 MB
1.TensorFlow Setup and Fundamental Concepts/04.TensorFlow Basics Part 2 - Graphs and Sessions.mp4 105.6 MB
1.TensorFlow Setup and Fundamental Concepts/05.TensorFlow Basics Part 3 - Training, Saving, and Restoring.mp4 103.9 MB
5.TensorFlow in Production/19.Requirements for ML at Scale.mp4 85.3 MB
5.TensorFlow in Production/20.TensorFlow with C++.mp4 78.2 MB
6.Miscellaneous Topics and Course Summary/26.Course Summary and Next Steps.mp4 71.3 MB
4.Tips and Tricks/15.TensorBoard.mp4 64.3 MB
1.TensorFlow Setup and Fundamental Concepts/02.Machine Learning Basics.mp4 63.9 MB
1.TensorFlow Setup and Fundamental Concepts/01.The Course Overview.mp4 53.0 MB
4.Tips and Tricks/17.Training Tips.mp4 40.8 MB
5.TensorFlow in Production/21.TensorFlow Serving.mp4 40.8 MB
4.Tips and Tricks/16.Working with Estimators.mp4 40.8 MB
2.Computer Vision/09.Training a CNN on CIFAR-10 – Part 2.mp4 37.9 MB
4.Tips and Tricks/18.Debugging Strategies.mp4 33.0 MB
2.Computer Vision/08.Training a CNN on CIFAR-10 – Part 1.mp4 25.3 MB
3.Natural Language Processing and Recurrent Neural Networks/13.Models for Text Classification – Part 1.mp4 24.4 MB
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16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4 92.5 MB
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18. Setting up your Environment/2. Windows-Focused Environment Setup 2018.mp4 203.4 MB
18. Setting up your Environment/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 175.4 MB
18. Setting up your Environment/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 174.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4 150.1 MB
13. Advanced Tensorflow Usage/2. Tensorflow Serving pt 2.mp4 130.5 MB
20. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).mp4 128.6 MB
20. Effective Learning Strategies for Machine Learning/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 122.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 108.2 MB
11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4 102.5 MB
4. Feedforward Artificial Neural Networks/4. Activation Functions.mp4 96.7 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.mp4 96.5 MB
5. Convolutional Neural Networks/5. CNN Architecture.mp4 95.4 MB
2. Google Colab/3. Uploading your own data to Google Colab.mp4 93.4 MB
20. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).mp4 92.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4 91.9 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 91.5 MB
10. GANs (Generative Adversarial Networks)/1. GAN Theory.mp4 90.7 MB
5. Convolutional Neural Networks/11. Improving CIFAR-10 Results.mp4 90.6 MB
5. Convolutional Neural Networks/6. CNN Code Preparation.mp4 90.5 MB
4. Feedforward Artificial Neural Networks/9. ANN for Regression.mp4 88.0 MB
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~Get Your Files Here !/1. Deep Learning Basics.mp4 173.0 MB
~Get Your Files Here !/12. Transfer Learning.mp4 136.6 MB
~Get Your Files Here !/2. Basic Maths for Deep Learning.mp4 117.8 MB
~Get Your Files Here !/14. Augmentation.mp4 115.1 MB
~Get Your Files Here !/9. Augmentation Technique.mp4 115.1 MB
~Get Your Files Here !/16. Recurrent neural networks.mp4 109.2 MB
~Get Your Files Here !/3. Python Introduction.mp4 76.1 MB
~Get Your Files Here !/10. Deep Learning Part 1.mp4 68.9 MB
~Get Your Files Here !/17. Long Short-Term Memory RNN.mp4 68.8 MB
~Get Your Files Here !/13. TensorBoard.mp4 61.6 MB
~Get Your Files Here !/11. Deep Learning Part 2.mp4 58.3 MB
~Get Your Files Here !/5. Set Data Type.mp4 54.9 MB
~Get Your Files Here !/6. Convolutional Neural Network.mp4 53.3 MB
~Get Your Files Here !/7. Adam's Optimiser.mp4 38.0 MB
~Get Your Files Here !/4. List Tuple Data Types.mp4 38.0 MB
~Get Your Files Here !/8. Custom CallBacks.mp4 35.5 MB
~Get Your Files Here !/15. Bi- Directional RNN.mp4 33.1 MB
~Get Your Files Here !/1. Deep Learning Basics.srt 44.1 kB
~Get Your Files Here !/2. Basic Maths for Deep Learning.srt 30.7 kB
~Get Your Files Here !/3. Python Introduction.srt 23.3 kB
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