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【压缩文件】 [ FreeCourseWeb.com ] A Practical Guide to Machine Learning with TensorFlow 2.0 & Keras.zip

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[ FreeCourseWeb.com ] A Practical Guide to Machine Learning with TensorFlow 2.0 & Keras.zip 2.4 GB

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【文档书籍】 21个项目玩转深度学习：基于TensorFlow的实践详解(高清完整版-带书签).pdf

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21个项目玩转深度学习：基于TensorFlow的实践详解(高清完整版-带书签).pdf 150.9 MB

猜你喜欢：完整版 pdf 21 TensorFlow 书签玩转详解高清深度实践

【影视】 Tensorflow 2.0 Um Guia Completo sobre o novo TensorFlow

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16. Anexo III - Redes Neurais Recorrentes - teoria/4. Intuição prática.mp4 166.4 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/3. Long short term memory - LSTM.mp4 104.1 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/1. O que são Redes Neurais Recorrentes.mp4 103.1 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/2. A Equação de Bellman.mp4 95.1 MB
14. Anexo I - Redes Neurais Artificiais - teoria/9. Funções de ativação II.mp4 81.5 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/2. Introdução a redes neurais convolucionais II.mp4 80.5 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/1. Introdução a redes neurais convolucionais I.mp4 75.9 MB
7. Aprendizagem por Reforço Profunda para Negociação no Mercado de Ações/12. Treinamento II.mp4 75.6 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/11. Replay de Experiência.mp4 75.2 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/12. Políticas de Seleções de Ações.mp4 74.6 MB
2. Básico do TensorFlow/1. Do TensorFlow 1.x para o TensorFlow 2.0 - Constantes, variáveis e tensores.mp4 72.9 MB
1. Introdução/1. Bem-vindo(a) ao curso!.mp4 72.3 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/2. Problema do gradiente desaparecendo (vanish gradient problem).mp4 71.0 MB
10. API com Flask e TensorFlow 2.0/1. Configuração do Projeto.mp4 70.3 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/4. Markov Decision Process - MDP.mp4 70.3 MB
5. Redes Neurais Recorrentes/1. Configuração do Projeto e Pré-processamento.mp4 66.1 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/6. Etapa 3 - flattening.mp4 65.8 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/7. Etapa 4 - rede neural densa.mp4 65.3 MB
9. Pré-processamento de Dados com TFT (TensorFlow Transform)/5. Pipeline de Pré-processamento.mp4 63.7 MB
7. Aprendizagem por Reforço Profunda para Negociação no Mercado de Ações/6. IA Trader 5.mp4 63.4 MB

猜你喜欢： novo Completo Um sobre TensorFlow Tensorflow 2.0 Guia

【影视】 [Tutorialsplanet.NET] Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence

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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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【影视】 [FreeCourseSite.com] 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】 [DesireCourse.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

猜你喜欢： DesireCourse Deep Udemy 2020 Learning TensorFlow Net 2.0

【压缩文件】 [ FreeCourseWeb.com ] PluralSight - Build, Train, and Deploy Your First Neural Network with TensorFlow.zip

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[ FreeCourseWeb.com ] PluralSight - Build, Train, and Deploy Your First Neural Network with TensorFlow.zip 337.7 MB

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【影视】 desire-course.-net-udemy-tensorflow-2.0-deep-learning-and-artificial-intelligence_20200804

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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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【压缩文件】 [ FreeCourseWeb.com ] Hands-On Image Generation with TensorFlow - A practical guide to generating images and videos using deep learning.zip

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[ FreeCourseWeb.com ] Hands-On Image Generation with TensorFlow - A practical guide to generating images and videos using deep learning.zip 241.0 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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【压缩文件】 [FreeCourseSite.com] Udemy - TensorFlow 2.0 Practical Advanced

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[FreeCourseSite.com] Udemy - TensorFlow 2.0 Practical Advanced.part1.rar 2.1 GB
[FreeCourseSite.com] Udemy - TensorFlow 2.0 Practical Advanced.part2.rar 2.1 GB
[FreeCourseSite.com] Udemy - TensorFlow 2.0 Practical Advanced.part3.rar 729.6 MB

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【影视】 [Tutorialsplanet.NET] Udemy - Complete Tensorflow 2 And Keras Deep Learning Bootcamp

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9 - Recurrent Neural Networks RNNs/89 - Bonus Multivariate Time Series RNN and LSTMs.mp4 246.5 MB
1 - Course Overview Installs and Setup/3 - Course Setup and Installation.mp4 242.8 MB
9 - Recurrent Neural Networks RNNs/88 - RNN Exercise Solutions.mp4 240.8 MB
7 - Basic Artificial Neural Networks ANNs/58 - Tensorboard.mp4 236.0 MB
7 - Basic Artificial Neural Networks ANNs/51 - Keras Project Solutions Exploratory Data Analysis.mp4 230.7 MB
13 - Deployment/116 - Live Deployment to the Web.mp4 204.9 MB
9 - Recurrent Neural Networks RNNs/86 - RNN on a Time Series Part Two.mp4 204.9 MB
7 - Basic Artificial Neural Networks ANNs/43 - Keras Regression Code Along Exploratory Data Analysis.mp4 200.3 MB
12 - Generative Adversarial Networks/107 - Creating a GAN Part Three Model Training.mp4 181.3 MB
7 - Basic Artificial Neural Networks ANNs/48 - Keras Classification Dealing with Overfitting and Evaluation.mp4 179.4 MB
13 - Deployment/115 - Flask Front End.mp4 175.6 MB
11 - AutoEncoders/99 - Autoencoder for Dimensionality Reduction.mp4 175.4 MB
4 - Pandas Crash Course/18 - Data Input and Output.mp4 159.1 MB
8 - Convolutional Neural Networks CNNs/72 - CNN on Real Image Files Part Three Creating the Model.mp4 141.9 MB
7 - Basic Artificial Neural Networks ANNs/52 - Keras Project Solutions Dealing with Missing Data.mp4 139.8 MB
7 - Basic Artificial Neural Networks ANNs/41 - Keras Syntax Basics Part Two Creating and Training the Model.mp4 131.0 MB
13 - Deployment/110 - Creating the Model.mp4 128.0 MB
5 - Visualization Crash Course/23 - Seaborn Basics.mp4 125.8 MB
7 - Basic Artificial Neural Networks ANNs/53 - Keras Project Solutions Dealing with Missing Data Part Two.mp4 124.3 MB
8 - Convolutional Neural Networks CNNs/71 - CNN on Real Image Files Part Two Data Processing.mp4 123.9 MB

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【压缩文件】 [ FreeCourseWeb.com ] End-to-End Machine Learning with TensorFlow on GCP.zip

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[ FreeCourseWeb.com ] End-to-End Machine Learning with TensorFlow on GCP.zip 470.9 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】 [FreeCourseSite.com] 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】 [FreeCourseLab.me] Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence

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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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【影视】 [FreeTutorials.Us] deep-learning-convolutional-neural-networks-theano-tensorflow

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07 Project Facial Expression Recognition/026 Convolutional Net in Theano.mp4 54.2 MB
07 Project Facial Expression Recognition/027 Convolutional Net in TensorFlow.mp4 50.0 MB
08 Appendix/028 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 46.0 MB
04 Convolutional Neural Network in Theano/018 Theano - Full CNN and Test on SVHN.mp4 41.3 MB
08 Appendix/029 How to Code by Yourself part 1.mp4 25.7 MB
05 Convolutional Neural Network in TensorFlow/021 TensorFlow - Full CNN and Test on SVHN.mp4 25.2 MB
03 Convolutional Neural Network Description/016 LeNet - How the Shapes Go Together.mp4 22.7 MB
07 Project Facial Expression Recognition/023 Facial Expression Recognition Problem Description.mp4 22.5 MB
02 Convolution/010 Write Convolution Yourself.mp4 19.4 MB
08 Appendix/030 How to Code by Yourself part 2.mp4 15.5 MB
02 Convolution/008 Convolution example with images Gaussian Blur.mp4 14.7 MB
07 Project Facial Expression Recognition/025 Utilities walkthrough.mp4 14.1 MB
02 Convolution/007 Convolution example with audio Echo.mp4 12.7 MB
07 Project Facial Expression Recognition/024 The class imbalance problem.mp4 10.6 MB
01 Outline and Review/005 How to load the SVHN data and benchmark a vanilla deep network.mp4 10.5 MB
02 Convolution/011 Alternative Views on Convolution.mp4 10.3 MB
01 Outline and Review/004 How to Succeed in this Course.mp4 10.0 MB
04 Convolutional Neural Network in Theano/019 Visualizing the Learned Filters.mp4 9.4 MB
02 Convolution/006 What is convolution.mp4 9.0 MB
03 Convolutional Neural Network Description/013 Architecture of a CNN.mp4 8.9 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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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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