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- 【压缩文件】 [Udemy] Complete Guide to TensorFlow for Deep Learning with Python (2020) [En]
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1. Introduction/2.1 FULL_TENSORFLOW_NOTES__AND_DATA.zip 314.2 MB
1. Introduction/3.1 FULL_TENSORFLOW_NOTES__AND_DATA.zip 314.2 MB
6. TensorFlow Basics/8. TensorFlow Regression Example _ Part Two.mp4 60.6 MB
7. Convolutional Neural Networks/13. CNN Project Exercise Solution - Part One.mp4 52.6 MB
8. Recurrent Neural Networks/13. Quick Note on Word2Vec.srt 47.1 MB
10. AutoEncoders/5. Stacked Autoencoder.mp4 46.1 MB
5. Introduction to Neural Networks/11. Manual Neural Network Classification Task.mp4 42.5 MB
9. Miscellaneous Topics/6. Tensorboard.mp4 41.9 MB
10. AutoEncoders/2. Dimensionality Reduction with Linear Autoencoder.mp4 39.4 MB
11. Reinforcement Learning with OpenAI Gym/8. Simple Neural Network Game.mp4 37.6 MB
8. Recurrent Neural Networks/15. Word2Vec Code Along - Part One.mp4 37.3 MB
8. Recurrent Neural Networks/12. Time Series Exercise Solution.mp4 36.8 MB
7. Convolutional Neural Networks/7. MNIST Basic Approach Part Two.mp4 36.6 MB
8. Recurrent Neural Networks/7. RNN with TensorFlow - Part One.mp4 35.8 MB
8. Recurrent Neural Networks/16. Word2Vec Part Two.mp4 35.0 MB
9. Miscellaneous Topics/4. Deep Nets with Tensorflow Abstractions API - Keras.mp4 35.0 MB
11. Reinforcement Learning with OpenAI Gym/11. Policy Gradient Code Along Part Two.mp4 34.4 MB
6. TensorFlow Basics/6. TensorFlow - A Neural Network - Part Two.mp4 34.1 MB
4. Crash Course Overview/2. NumPy Crash Course.mp4 34.1 MB
6. TensorFlow Basics/10. TensorFlow Classification Example - Part Two.mp4 33.5 MB
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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
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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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- 【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】 [FreeCourseSite.com] 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】 [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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- 【压缩文件】 [ FreeCourseWeb.com ] A Practical Guide to Deep Learning with TensorFlow 2.0 and Keras.zip
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[ FreeCourseWeb.com ] A Practical Guide to Deep Learning with TensorFlow 2.0 and Keras.zip 4.3 GB
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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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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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01 Course Overview Installs and Setup/002 Course Setup and Installation.mp4 159.8 MB
13 Deployment/114 Flask Front End.mp4 156.9 MB
09 Recurrent Neural Networks - RNNs/088 Bonus - Multivariate Time Series - RNN and LSTMs.mp4 156.6 MB
09 Recurrent Neural Networks - RNNs/087 RNN Exercise - Solutions.mp4 155.3 MB
07 Basic Artificial Neural Networks - ANNs/057 Tensorboard.mp4 151.2 MB
07 Basic Artificial Neural Networks - ANNs/050 Keras Project Solutions - Exploratory Data Analysis.mp4 150.6 MB
07 Basic Artificial Neural Networks - ANNs/042 Keras Regression Code Along - Exploratory Data Analysis.mp4 143.7 MB
12 Generative Adversarial Networks/106 Creating a GAN - Part Three - Model Training.mp4 138.0 MB
09 Recurrent Neural Networks - RNNs/085 RNN on a Time Series - Part Two.mp4 137.4 MB
13 Deployment/115 Live Deployment to the Web.mp4 132.7 MB
07 Basic Artificial Neural Networks - ANNs/053 Keras Project Solutions - Categorical Data.mp4 131.1 MB
11 AutoEncoders/098 Autoencoder for Dimensionality Reduction.mp4 123.2 MB
07 Basic Artificial Neural Networks - ANNs/047 Keras Classification - Dealing with Overfitting and Evaluation.mp4 116.7 MB
01 Course Overview Installs and Setup/002 FINAL-TF2-FILES.zip 104.1 MB
01 Course Overview Installs and Setup/003 FINAL-TF2-FILES.zip 104.1 MB
08 Convolutional Neural Networks - CNNs/064 CNN on MNIST - Part Two - Creating and Training the Model.mp4 103.7 MB
07 Basic Artificial Neural Networks - ANNs/051 Keras Project Solutions - Dealing with Missing Data.mp4 101.5 MB
11 AutoEncoders/099 Autoencoder for Images - Part One.mp4 98.7 MB
04 Pandas Crash Course/017 Data Input and Output.mp4 98.0 MB
05 Visualization Crash Course/022 Seaborn Basics.mp4 96.3 MB
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[ FreeCourseWeb.com ] Skillshare - What are Tensors in Tensorflow- Master the basics.zip 724.4 MB
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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
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01 Introduction/001 Introduction.mp4 12.5 MB
01 Introduction/001 Introduction-subtitle-en.vtt 4.0 kB
01 Introduction/002 Course Overview -- PLEASE DON'T SKIP THIS LECTURE! Thanks _).mp4 17.2 MB
01 Introduction/002 Course Overview -- PLEASE DON'T SKIP THIS LECTURE! Thanks _)-subtitle-en.vtt 14.8 kB
01 Introduction/002 FULL-TENSORFLOW-NOTES-AND-DATA.zip 314.2 MB
01 Introduction/003 FULL-TENSORFLOW-NOTES-AND-DATA.zip 314.2 MB
02 Installation and Setup/005 Installing TensorFlow Environment.mp4 29.2 MB
02 Installation and Setup/005 Installing TensorFlow Environment-subtitle-en.vtt 17.5 kB
03 What is Machine Learning_/006 Machine Learning Overview.mp4 31.9 MB
03 What is Machine Learning_/006 Machine Learning Overview-subtitle-en.vtt 24.1 kB
03 What is Machine Learning_/external_links.txt 132 Bytes
04 Crash Course Overview/007 Crash Course Section Introduction.mp4 2.3 MB
04 Crash Course Overview/007 Crash Course Section Introduction-subtitle-en.vtt 1.8 kB
04 Crash Course Overview/008 NumPy Crash Course.mp4 34.1 MB
04 Crash Course Overview/008 NumPy Crash Course-subtitle-en.vtt 20.7 kB
04 Crash Course Overview/009 Pandas Crash Course.mp4 9.5 MB
04 Crash Course Overview/009 Pandas Crash Course-subtitle-en.vtt 6.0 kB
04 Crash Course Overview/010 Data Visualization Crash Course.mp4 20.5 MB
04 Crash Course Overview/010 Data Visualization Crash Course-subtitle-en.vtt 10.3 kB
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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
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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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