tensorflow - 磁力管家 - 男人都爱上的磁力连接搜索引擎

【影视】 Accelerating TensorFlow with the Google Machine Learning Engine

收录时间:2018-07-28 文档个数:84 文档大小:356.8 MB 最近下载:2025-05-15 人气:759 磁力链接

3.3. Training TensorFlow Applications/18.Linear regression in code - Part 2.mp4 23.2 MB
0.Introduction/01.Welcome.mp4 5.1 MB
0.Introduction/02.What you should know.en.srt 3.2 kB
0.Introduction/02.What you should know.mp4 2.8 MB
0.Introduction/03.Using the exercise files.en.srt 1.7 kB
0.Introduction/03.Using the exercise files.mp4 2.2 MB
1.1. Introducing TensorFlow/04.Overview and installation.en.srt 5.7 kB
1.1. Introducing TensorFlow/04.Overview and installation.mp4 5.4 MB
1.1. Introducing TensorFlow/05.Getting started.en.srt 4.7 kB
1.1. Introducing TensorFlow/05.Getting started.mp4 3.9 MB
1.1. Introducing TensorFlow/06.Running a simple application.en.srt 3.5 kB
1.1. Introducing TensorFlow/06.Running a simple application.mp4 6.2 MB
2.2. Fundamentals of TensorFlow Development/07.Creating tensors.en.srt 8.3 kB
2.2. Fundamentals of TensorFlow Development/07.Creating tensors.mp4 6.5 MB
2.2. Fundamentals of TensorFlow Development/08.Basic tensor operations.en.srt 5.7 kB
2.2. Fundamentals of TensorFlow Development/08.Basic tensor operations.mp4 4.5 MB
2.2. Fundamentals of TensorFlow Development/09.Advanced tensor operations.en.srt 5.2 kB
2.2. Fundamentals of TensorFlow Development/09.Advanced tensor operations.mp4 4.3 MB
2.2. Fundamentals of TensorFlow Development/10.Understanding graphs and sessions.en.srt 6.9 kB
2.2. Fundamentals of TensorFlow Development/10.Understanding graphs and sessions.mp4 5.4 MB

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【影视】 [Tutorialsplanet.NET] Udemy - Deep Learning with TensorFlow 2.0 [2020]

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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
13. Business case/4. Preprocessing the data.mp4 88.4 MB
13. Business case/1. Exploring the dataset and identifying predictors.mp4 69.5 MB
13. Business case/9. Setting an early stopping mechanism.mp4 52.2 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
12. The MNIST example/6. Preprocess the data - shuffle and batch the data.mp4 43.6 MB
12. The MNIST example/10. Learning.mp4 42.9 MB
2. Introduction to neural networks/24. N-parameter gradient descent.mp4 41.4 MB
3. Setting up the working environment/9. Installing TensorFlow 2.mp4 40.6 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
5. TensorFlow - An introduction/5. Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.mp4 36.4 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
5. TensorFlow - An introduction/1. TensorFlow outline.mp4 35.2 MB
14. Appendix Linear Algebra Fundamentals/6. Addition and Subtraction of Matrices.mp4 34.2 MB
3. Setting up the working environment/2. Why Python and why Jupyter.mp4 33.6 MB
13. Business case/8. Learning and interpreting the result.mp4 32.7 MB

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【影视】 [GigaCourse.Com] Udemy - TensorFlow Developer Certificate in 2021 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 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】 [DesireCourse.Net] Udemy - Master Deep Learning with TensorFlow in Python

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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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【影视】 IA Expert - TensorFlow Machine Learning e Deep Learning com Python

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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】 365 Data Science - Deep Learning with TensorFlow 2.0 [CoursesGhar]

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13. Business case/4. Preprocessing the data.mp4 81.2 MB
14. Conclusion/3. An overview of CNNs.mp4 75.4 MB
6. Deep nets overview/3. Really understand deep nets.mp4 61.0 MB
2. Neural networks Intro/11. One-parameter gradient descent.mp4 59.1 MB
6. Deep nets overview/7. Backpropagation.mp4 55.3 MB
13. Business case/1. Exploring the dataset and identifying predictors.mp4 54.6 MB
2. Neural networks Intro/12. N-parameter gradient descent.mp4 52.5 MB
1. Introduction/2. What does the course cover.mp4 51.6 MB
14. Conclusion/1. Summary.mp4 50.9 MB
4. Minimal example/4. Training the model.mp4 48.8 MB
13. Business case/3. Balancing the dataset.mp4 46.8 MB
13. Business case/7. Setting an early stopping mechanism.mp4 44.7 MB
2. Neural networks Intro/1. Introduction to neural networks.mp4 44.6 MB
2. Neural networks Intro/6. The linear model. Multiple inputs and multiple outputs.mp4 44.3 MB
14. Conclusion/5. Non-NN approaches.mp4 43.9 MB
5. Introduction to TensorFlow 2/1. TensorFlow outline.mp4 43.2 MB
12. Deeper example/8. Learning.mp4 42.9 MB
2. Neural networks Intro/3. Types of machine learning.mp4 42.8 MB
11. Preprocessing/3. Standardization.mp4 42.3 MB
6. Deep nets overview/4. Why do we need non-linearities.mp4 39.8 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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【影视】 PacktPub - Master Deep Learning with TensorFlow 2.0 in Python [2019] [Video]

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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

猜你喜欢： Python Video Deep 2019 PacktPub Master Learning TensorFlow 2.0

【影视】 [ FreeCourseWeb.com ] TutsPlus - Learn Machine Learning With Google TensorFlow

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~Get Your Files Here !/2. Creating Deep Neural Networks/2.3 Using Real-World Data With a Neural Network.mp4 53.8 MB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.4 Creating a Convolutional Network for Image Classification.mp4 47.7 MB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.5 Training and Using a Convolutional Network.mp4 36.2 MB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.2 Training and Using Your Neural Network.mp4 34.3 MB
~Get Your Files Here !/1. Introduction/1.3 Setting Up TensorFlow.mp4 33.0 MB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.1 Creating Your First Neural Network.mp4 26.6 MB
~Get Your Files Here !/1. Introduction/1.2 Why Use TensorFlow.mp4 18.2 MB
~Get Your Files Here !/3. Conclusion/3.1 Conclusion.mp4 10.3 MB
~Get Your Files Here !/1. Introduction/1.1 Introduction.mp4 10.0 MB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.4 Creating a Convolutional Network for Image Classification.vtt 12.5 kB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.3 Using Real-World Data With a Neural Network.vtt 11.3 kB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.1 Creating Your First Neural Network.vtt 10.1 kB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.2 Training and Using Your Neural Network.vtt 7.6 kB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.5 Training and Using a Convolutional Network.vtt 4.7 kB
~Get Your Files Here !/1. Introduction/1.2 Why Use TensorFlow.vtt 2.9 kB
~Get Your Files Here !/1. Introduction/1.3 Setting Up TensorFlow.vtt 2.8 kB
~Get Your Files Here !/3. Conclusion/3.1 Conclusion.vtt 1.3 kB
~Get Your Files Here !/1. Introduction/1.1 Introduction.vtt 1.3 kB
~Get Your Files Here !/Bonus Resources.txt 357 Bytes
Get Bonus Downloads Here.url 183 Bytes

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【影视】 [FreeCourseSite.com] Udemy - TensorFlow 2.0 Practical Advanced

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01 - INTRODUCTION AND COURSE OUTLINE/007 Whats New in TensorFlow 2.0.mp4 229.6 MB
05 - DEEP DREAM/008 Deep Dream Coding P5.mp4 221.2 MB
05 - DEEP DREAM/001 What is Deep Dream.mp4 203.4 MB
05 - DEEP DREAM/002 How does DeepDream Algo work.mp4 162.6 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/001 ANN and CNN - Part 1.mp4 149.3 MB
04 - AUTOENCODERS/013 Autoencoders Project 2 - Coding P2.mp4 147.5 MB
04 - AUTOENCODERS/001 Autoencoders intuition.mp4 124.4 MB
04 - AUTOENCODERS/20087012-traffic-signs-data.zip 121.4 MB
03 - TRANSFER LEARNING (TF HUB)/006 Transfer Learning Project 1 - Coding P2.mp4 114.9 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/010 Project 1 - Solution Part 2.mp4 106.3 MB
06 - GANs/010 GANS Project 1 P5.mp4 102.1 MB
08 - TENSORFLOW SERVING AND TENSORBOARD/003 TF Serving Coding Part 3.mp4 102.1 MB
05 - DEEP DREAM/007 Deep Dream Coding P4.mp4 101.9 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/007 ANN and CNN - Part 7.mp4 100.3 MB
07 - RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs/006 Vanishing Gradient Problem.mp4 100.3 MB
07 - RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs/007 Long Short Term Memory LSTM.mp4 96.7 MB
01 - INTRODUCTION AND COURSE OUTLINE/004 ML, AI and DL.mp4 96.2 MB
06 - GANs/001 GANS intuition.mp4 95.4 MB
03 - TRANSFER LEARNING (TF HUB)/005 Transfer Learning Project 1 - Coding P1.mp4 93.8 MB
03 - TRANSFER LEARNING (TF HUB)/007 Transfer Learning Project 1 - Coding P3.mp4 92.6 MB

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【影视】 [FreeTutorials.Us] data-science-deep-learning-in-theano-tensorflow

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01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/001 Outline - what did you learn previously and what will you learn in this course.mp4 4.9 MB
01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/002 Where does this course fit into your deep learning studies.mp4 6.3 MB
01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/003 How to Succeed in this Course.mp4 9.2 MB
01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/004 Where to get the MNIST dataset and Establishing a Linear Benchmark.mp4 11.7 MB
02 Gradient Descent Full vs Batch vs Stochastic/005 What are full batch and stochastic gradient descent.mp4 6.1 MB
02 Gradient Descent Full vs Batch vs Stochastic/006 Full vs Batch vs Stochastic Gradient Descent in code.mp4 14.7 MB
03 Momentum and adaptive learning rates/007 Momentum.mp4 3.3 MB
03 Momentum and adaptive learning rates/008 Code for training a neural network using momentum.mp4 15.3 MB
03 Momentum and adaptive learning rates/009 Variable and adaptive learning rates.mp4 5.3 MB
03 Momentum and adaptive learning rates/010 Constant learning rate vs. RMSProp in Code.mp4 11.5 MB
04 Choosing Hyperparameters/011 Hyperparameter Optimization Cross-validation Grid Search and Random Search.mp4 5.8 MB
04 Choosing Hyperparameters/012 Grid Search in Code.mp4 14.4 MB
04 Choosing Hyperparameters/013 Random Search in Code.mp4 8.3 MB
05 Theano/014 Theano Basics Variables Functions Expressions Optimization.mp4 20.3 MB
05 Theano/015 Building a neural network in Theano.mp4 22.8 MB
06 TensorFlow/016 TensorFlow Basics Variables Functions Expressions Optimization.mp4 17.9 MB
06 TensorFlow/017 Building a neural network in TensorFlow.mp4 25.0 MB
07 GPU Speedup Homework and Other Misc Topics/018 Setting up a GPU Instance on Amazon Web Services.mp4 26.9 MB
07 GPU Speedup Homework and Other Misc Topics/019 Can Big Data be used to Speed Up Backpropagation.mp4 5.5 MB
07 GPU Speedup Homework and Other Misc Topics/020 Exercises and Concepts Still to be Covered.mp4 4.7 MB

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【影视】 [FreeCourseSite.com] Udemy - TensorFlow Developer Certificate in 2022 Zero to Mastery

收录时间:2023-12-29 文档个数:954 文档大小:29.1 GB 最近下载:2025-05-15 人气:525 磁力链接

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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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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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
19. Appendix FAQ/9. What order should I take your courses in (part 2).mp4 128.6 MB
19. Appendix FAQ/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 96.6 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
19. Appendix FAQ/8. 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 90.5 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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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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Tensorflow源码级技术分享集/Tensorflow源码级技术分享【第10期】.mp4 191.7 MB
Tensorflow源码级技术分享集/Tensorflow源码级技术分享【第1期】.mp4 869.2 MB
Tensorflow源码级技术分享集/Tensorflow源码级技术分享【第2期】.mp4 1.1 GB
Tensorflow源码级技术分享集/Tensorflow源码级技术分享【第3期】.mp4 737.9 MB
Tensorflow源码级技术分享集/Tensorflow源码级技术分享【第4期】.mp4 1.0 GB
Tensorflow源码级技术分享集/Tensorflow源码级技术分享【第5期】.mp4 633.6 MB
Tensorflow源码级技术分享集/Tensorflow源码级技术分享【第6期】.mp4 1.5 GB
Tensorflow源码级技术分享集/Tensorflow源码级技术分享【第7期】.mp4 1.2 GB
Tensorflow源码级技术分享集/Tensorflow源码级技术分享【第8期】.mp4 521.7 MB
Tensorflow源码级技术分享集/Tensorflow源码级技术分享【第9期】.mp4 246.2 MB
Tensorflow视频教程/Tensorflow 1 why .mp4 3.2 MB
Tensorflow视频教程/Tensorflow 10 添加层.mp4 32.4 MB
Tensorflow视频教程/Tensorflow 11 建造神经网络.mp4 67.9 MB
Tensorflow视频教程/Tensorflow 12 结果可视化.mp4 23.5 MB
Tensorflow视频教程/Tensorflow 13 优化器.mp4 17.2 MB
Tensorflow视频教程/Tensorflow 14 可视化好帮手1.mp4 61.5 MB
Tensorflow视频教程/Tensorflow 15 可视化好帮手2.mp4 27.6 MB
Tensorflow视频教程/Tensorflow 16 分类学习.mp4 36.6 MB
Tensorflow视频教程/Tensorflow 17 dropout 解决overfitting 问题.mp4 44.2 MB
Tensorflow视频教程/Tensorflow 18-1 CNN卷积神经网络1.mp4 30.0 MB

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