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Tensorflow 2.0: Deep Learning and Artificial Intelligence

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Tensorflow 2.0: Deep Learning and Artificial Intelligence (Size: 6.83 GB)
  1. Welcome
  1. Introduction.mp4 34.81 MB
  1. Introduction.srt 5.7 KB
  2. Outline.mp4 73.67 MB
  2. Outline.srt 17.1 KB
  3. Where to get the code.mp4 62.91 MB
  3. Where to get the code.srt 15.36 KB
  3.1 Colab Notebooks.html 157 B
  3.2 Github Link.html 120 B
  10. GANs (Generative Adversarial Networks)
  1. GAN Theory.mp4 87.16 MB
  1. GAN Theory.srt 20.71 KB
  2. GAN Code.mp4 78.3 MB
  2. GAN Code.srt 14.88 KB
  11. Deep Reinforcement Learning (Theory)
  1. Deep Reinforcement Learning Section Introduction.mp4 38.05 MB
  1. Deep Reinforcement Learning Section Introduction.srt 8.6 KB
  10. Epsilon-Greedy.mp4 40.11 MB
  10. Epsilon-Greedy.srt 7.49 KB
  11. Q-Learning.mp4 61.83 MB
  11. Q-Learning.srt 17.91 KB
  12. Deep Q-Learning DQN (pt 1).mp4 56.27 MB
  12. Deep Q-Learning DQN (pt 1).srt 16.43 KB
  13. Deep Q-Learning DQN (pt 2).mp4 49.6 MB
  13. Deep Q-Learning DQN (pt 2).srt 13.21 KB
  14. How to Learn Reinforcement Learning.mp4 37.7 MB
  14. How to Learn Reinforcement Learning.srt 7.62 KB
  2. Elements of a Reinforcement Learning Problem.mp4 98.59 MB
  2. Elements of a Reinforcement Learning Problem.srt 26.19 KB
  3. States, Actions, Rewards, Policies.mp4 43.33 MB
  3. States, Actions, Rewards, Policies.srt 11.32 KB
  4. Markov Decision Processes (MDPs).mp4 49.35 MB
  4. Markov Decision Processes (MDPs).srt 12.65 KB
  5. The Return.mp4 21.13 MB
  5. The Return.srt 6.26 KB
  6. Value Functions and the Bellman Equation.mp4 43.56 MB
  6. Value Functions and the Bellman Equation.srt 12.51 KB
  7. What does it mean to “learn”.mp4 31.71 MB
  7. What does it mean to “learn”.srt 8.92 KB
  8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 42.74 MB
  8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt 12.41 KB
  9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 52.91 MB
  9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt 14.88 KB
  12. Stock Trading Project with Deep Reinforcement Learning
  1. Reinforcement Learning Stock Trader Introduction.mp4 26.04 MB
  1. Reinforcement Learning Stock Trader Introduction.srt 6.84 KB
  10. Help! Why is the code slower on my machine.mp4 42.46 MB
  10. Help! Why is the code slower on my machine.srt 11.72 KB
  2. Data and Environment.mp4 50.97 MB
  2. Data and Environment.srt 15.69 KB
  3. Replay Buffer.mp4 24.04 MB
  3. Replay Buffer.srt 6.94 KB
  4. Program Design and Layout.mp4 25.98 MB
  4. Program Design and Layout.srt 8.64 KB
  5. Code pt 1.mp4 39.55 MB
  5. Code pt 1.srt 7.21 KB
  6. Code pt 2.mp4 68 MB
  6. Code pt 2.srt 11.75 KB
  7. Code pt 3.mp4 52.05 MB
  7. Code pt 3.srt 7.75 KB
  8. Code pt 4.mp4 52.51 MB
  8. Code pt 4.srt 8.37 KB
  9. Reinforcement Learning Stock Trader Discussion.mp4 16.59 MB
  9. Reinforcement Learning Stock Trader Discussion.srt 4.39 KB
  13. Advanced Tensorflow Usage
  1. What is a Web Service (Tensorflow Serving pt 1).mp4 27.78 MB
  1. What is a Web Service (Tensorflow Serving pt 1).srt 7.71 KB
  2. Tensorflow Serving pt 2.mp4 104.99 MB
  2. Tensorflow Serving pt 2.srt 20.42 KB
  3. Tensorflow Lite (TFLite).mp4 42.59 MB
  3. Tensorflow Lite (TFLite).srt 11.03 KB
  4. Why is Google the King of Distributed Computing.mp4 44.93 MB
  4. Why is Google the King of Distributed Computing.srt 11.25 KB
  5. Training with Distributed Strategies.mp4 43.54 MB
  5. Training with Distributed Strategies.srt 8.53 KB
  6. Using the TPU.mp4 45.24 MB
  6. Using the TPU.srt 6.96 KB
  GetFreeCourses.Co.url 116 B
  How you can help GetFreeCourses.Co.txt 182 B
  14. Low-Level Tensorflow
  1. Differences Between Tensorflow 1.x and Tensorflow 2.x.mp4 38.68 MB
  1. Differences Between Tensorflow 1.x and Tensorflow 2.x.srt 12.2 KB
  2. Constants and Basic Computation.mp4 40.3 MB
  2. Constants and Basic Computation.srt 9.63 KB
  3. Variables and Gradient Tape.mp4 56.05 MB
  3. Variables and Gradient Tape.srt 13.58 KB
  4. Build Your Own Custom Model.mp4 58.55 MB
  4. Build Your Own Custom Model.srt 13.28 KB
  15. In-Depth Loss Functions
  1. Mean Squared Error.mp4 33.77 MB
  1. Mean Squared Error.srt 11.21 KB
  2. Binary Cross Entropy.mp4 23.68 MB
  2. Binary Cross Entropy.srt 7.26 KB
  3. Categorical Cross Entropy.mp4 31.7 MB
  3. Categorical Cross Entropy.srt 9.62 KB
  16. In-Depth Gradient Descent
  1. Gradient Descent.mp4 34.92 MB
  1. Gradient Descent.srt 9.77 KB
  2. Stochastic Gradient Descent.mp4 22.97 MB
  2. Stochastic Gradient Descent.srt 5.4 KB
  3. Momentum.mp4 34.25 MB
  3. Momentum.srt 7.84 KB
  4. Variable and Adaptive Learning Rates.mp4 34.85 MB
  4. Variable and Adaptive Learning Rates.srt 15.15 KB
  5. Adam (pt 1).mp4 55.12 MB
  5. Adam (pt 1).srt 16.67 KB
  6. Adam (pt 2).mp4 52.76 MB
  6. Adam (pt 2).srt 14.48 KB
  17. Extras
  1. How to Choose Hyperparameters.mp4 37.92 MB
  1. How to Choose Hyperparameters.srt 8.71 KB
  2. Where Are The Exercises.mp4 25.98 MB
  2. Where Are The Exercises.srt 5.41 KB
  3. Links to TF2.0 Notebooks.html 8.11 KB
  18. Setting up your Environment (FAQ by Student Request)
  1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 150.59 MB
  1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.69 KB
  2. Anaconda Environment Setup.mp4 180.9 MB
  2. Anaconda Environment Setup.srt 19.96 KB
  3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 167.3 MB
  3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.srt 32.01 KB
  19. Extra Help With Python Coding for Beginners (FAQ by Student Request)
  1. Beginner's Coding Tips.mp4 75.71 MB
  1. Beginner's Coding Tips.srt 19.02 KB
  2. How to Code Yourself (part 1).mp4 71.85 MB
  2. How to Code Yourself (part 1).srt 22.13 KB
  3. How to Code Yourself (part 2).mp4 49.14 MB
  3. How to Code Yourself (part 2).srt 12.98 KB
  4. Proof that using Jupyter Notebook is the same as not using it.mp4 69.45 MB
  4. Proof that using Jupyter Notebook is the same as not using it.srt 14.22 KB
  5. Is Theano Dead.mp4 40.76 MB
  5. Is Theano Dead.srt 12.63 KB
  GetFreeCourses.Co.url 116 B
  2. Google Colab
  1. Intro to Google Colab, how to use a GPU or TPU for free.mp4 53.84 MB
  1. Intro to Google Colab, how to use a GPU or TPU for free.srt 14.13 KB
  2. Tensorflow 2.0 in Google Colab.mp4 40.65 MB
  2. Tensorflow 2.0 in Google Colab.srt 9.48 KB
  3. Uploading your own data to Google Colab.mp4 73.59 MB
  3. Uploading your own data to Google Colab.srt 11.98 KB
  4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4 38.93 MB
  4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.srt 11.53 KB
  5. How to Succeed in this Course.mp4 43.75 MB
  5. How to Succeed in this Course.srt 8.28 KB
  20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)
  1. How to Succeed in this Course (Long Version).mp4 35.22 MB
  1. How to Succeed in this Course (Long Version).srt 14.61 KB
  2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 105.61 MB
  2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 31.63 KB
  3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 79.71 MB
  3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt 16.11 KB
  4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 108.17 MB
  4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt 23.01 KB
  21. Appendix FAQ Finale
  1. What is the Appendix.mp4 16.38 MB
  1. What is the Appendix.srt 3.75 KB
  2. BONUS Lecture.mp4 37.79 MB
  2. BONUS Lecture.srt 7.87 KB
  3. Machine Learning and Neurons
  1. What is Machine Learning.mp4 65.5 MB
  1. What is Machine Learning.srt 18.45 KB
  10. Why Keras.mp4 26.51 MB
  10. Why Keras.srt 5.77 KB
  11. Suggestion Box.mp4 27.12 MB
  11. Suggestion Box.srt 4.75 KB
  2. Code Preparation (Classification Theory).mp4 59.8 MB
  2. Code Preparation (Classification Theory).srt 20.26 KB
  3. Classification Notebook.mp4 54.54 MB
  3. Classification Notebook.srt 9.4 KB
  4. Code Preparation (Regression Theory).mp4 27.29 MB
  4. Code Preparation (Regression Theory).srt 9.07 KB
  5. Regression Notebook.mp4 57.47 MB
  5. Regression Notebook.srt 12.13 KB
  6. The Neuron.mp4 42.57 MB
  6. The Neuron.srt 12.46 KB
  7. How does a model learn.mp4 47.95 MB
  7. How does a model learn.srt 14 KB
  8. Making Predictions.mp4 33.88 MB
  8. Making Predictions.srt 7.99 KB
  9. Saving and Loading a Model.mp4 29.73 MB
  9. Saving and Loading a Model.srt 4.93 KB
  4. Feedforward Artificial Neural Networks
  1. Artificial Neural Networks Section Introduction.mp4 29.82 MB
  1. Artificial Neural Networks Section Introduction.srt 7.9 KB
  10. ANN for Regression.mp4 69.27 MB
  10. ANN for Regression.srt 12.78 KB
  2. Beginners Rejoice The Math in This Course is Optional.mp4 68.52 MB
  2. Beginners Rejoice The Math in This Course is Optional.srt 17.02 KB
  3. Forward Propagation.mp4 46.7 MB
  3. Forward Propagation.srt 12.2 KB
  4. The Geometrical Picture.mp4 56.43 MB
  4. The Geometrical Picture.srt 11.51 KB
  5. Activation Functions.mp4 80.54 MB
  5. Activation Functions.srt 22.64 KB
  6. Multiclass Classification.mp4 41.38 MB
  6. Multiclass Classification.srt 10.98 KB
  7. How to Represent Images.mp4 70.46 MB
  7. How to Represent Images.srt 15.6 KB
  8. Code Preparation (ANN).mp4 50.92 MB
  8. Code Preparation (ANN).srt 16.3 KB
  9. ANN for Image Classification.mp4 47.71 MB
  9. ANN for Image Classification.srt 9.93 KB
  5. Convolutional Neural Networks
  1. What is Convolution (part 1).mp4 79.77 MB
  1. What is Convolution (part 1).srt 20.16 KB
  10. Batch Normalization.mp4 21.11 MB
  10. Batch Normalization.srt 6.53 KB
  11. Improving CIFAR-10 Results.mp4 72.91 MB
  11. Improving CIFAR-10 Results.srt 13.17 KB
  2. What is Convolution (part 2).mp4 22.27 MB
  2. What is Convolution (part 2).srt 7.25 KB
  3. What is Convolution (part 3).mp4 27.64 MB
  3. What is Convolution (part 3).srt 8.01 KB
  4. Convolution on Color Images.mp4 69.44 MB
  4. Convolution on Color Images.srt 20.56 KB
  5. CNN Architecture.mp4 80.58 MB
  5. CNN Architecture.srt 27.89 KB
  6. CNN Code Preparation.mp4 76.88 MB
  6. CNN Code Preparation.srt 19.65 KB
  7. CNN for Fashion MNIST.mp4 42.79 MB
  7. CNN for Fashion MNIST.srt 7.99 KB
  8. CNN for CIFAR-10.mp4 29.69 MB
  8. CNN for CIFAR-10.srt 5.38 KB
  9. Data Augmentation.mp4 34.95 MB
  9. Data Augmentation.srt 11.24 KB
  GetFreeCourses.Co.url 116 B
  How you can help GetFreeCourses.Co.txt 182 B
  6. Recurrent Neural Networks, Time Series, and Sequence Data
  1. Sequence Data.mp4 90.15 MB
  1. Sequence Data.srt 24.02 KB
  10. GRU and LSTM (pt 2).mp4 50.36 MB
  10. GRU and LSTM (pt 2).srt 14.28 KB
  11. A More Challenging Sequence.mp4 64.65 MB
  11. A More Challenging Sequence.srt 9.6 KB
  12. Demo of the Long Distance Problem.mp4 124.05 MB
  12. Demo of the Long Distance Problem.srt 23.06 KB
  13. RNN for Image Classification (Theory).mp4 29.12 MB
  13. RNN for Image Classification (Theory).srt 5.99 KB
  14. RNN for Image Classification (Code).mp4 23.3 MB
  14. RNN for Image Classification (Code).srt 4.19 KB
  15. Stock Return Predictions using LSTMs (pt 1).mp4 67.11 MB
  15. Stock Return Predictions using LSTMs (pt 1).srt 15.71 KB
  16. Stock Return Predictions using LSTMs (pt 2).mp4 32.97 MB
  16. Stock Return Predictions using LSTMs (pt 2).srt 6.5 KB
  17. Stock Return Predictions using LSTMs (pt 3).mp4 67.34 MB
  17. Stock Return Predictions using LSTMs (pt 3).srt 14.42 KB
  18. Other Ways to Forecast.mp4 28.33 MB
  18. Other Ways to Forecast.srt 7.18 KB
  2. Forecasting.mp4 46.75 MB
  2. Forecasting.srt 13.35 KB
  3. Autoregressive Linear Model for Time Series Prediction.mp4 71.7 MB
  3. Autoregressive Linear Model for Time Series Prediction.srt 14.23 KB
  4. Proof that the Linear Model Works.mp4 16.2 MB
  4. Proof that the Linear Model Works.srt 4.56 KB
  5. Recurrent Neural Networks.mp4 83 MB
  5. Recurrent Neural Networks.srt 25.59 KB
  6. RNN Code Preparation.mp4 18.43 MB
  6. RNN Code Preparation.srt 7.14 KB
  7. RNN for Time Series Prediction.mp4 74.07 MB
  7. RNN for Time Series Prediction.srt 11.21 KB
  8. Paying Attention to Shapes.mp4 52.48 MB
  8. Paying Attention to Shapes.srt 9.88 KB
  9. GRU and LSTM (pt 1).mp4 79.86 MB
  9. GRU and LSTM (pt 1).srt 22.8 KB
  7. Natural Language Processing (NLP)
  1. Embeddings.mp4 52.56 MB
  1. Embeddings.srt 16.2 KB
  2. Code Preparation (NLP).mp4 57.04 MB
  2. Code Preparation (NLP).srt 16.82 KB
  3. Text Preprocessing.mp4 28.76 MB
  3. Text Preprocessing.srt 6.15 KB
  4. Text Classification with LSTMs.mp4 50.68 MB
  4. Text Classification with LSTMs.srt 9.8 KB
  5. CNNs for Text.mp4 40.4 MB
  5. CNNs for Text.srt 10.09 KB
  6. Text Classification with CNNs.mp4 39.62 MB
  6. Text Classification with CNNs.srt 6.63 KB
  8. Recommender Systems
  1. Recommender Systems with Deep Learning Theory.mp4 68.66 MB
  1. Recommender Systems with Deep Learning Theory.srt 17.4 KB
  2. Recommender Systems with Deep Learning Code.mp4 58.81 MB
  2. Recommender Systems with Deep Learning Code.srt 11.7 KB
  9. Transfer Learning for Computer Vision
  1. Transfer Learning Theory.mp4 55.13 MB
  1. Transfer Learning Theory.srt 10.66 KB
  2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4 31.57 MB
  2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).srt 7.29 KB
  3. Large Datasets and Data Generators.mp4 36.56 MB
  3. Large Datasets and Data Generators.srt 8.8 KB
  4. 2 Approaches to Transfer Learning.mp4 20.58 MB
  4. 2 Approaches to Transfer Learning.srt 5.96 KB
  5. Transfer Learning Code (pt 1).mp4 66.52 MB
  5. Transfer Learning Code (pt 1).srt 13.76 KB
  6. Transfer Learning Code (pt 2).mp4 46.05 MB
  6. Transfer Learning Code (pt 2).srt 10.43 KB
  Download Paid Udemy Courses For Free.url 116 B
  GetFreeCourses.Co.url 116 B
  How you can help GetFreeCourses.Co.txt 182 B
  ▲ 277 total files

Description


Tensorflow 2.0: Deep Learning and Artificial Intelligence

Machine Learning & Neural Networks for Computer Vision, Time Series Analysis, NLP, GANs, Reinforcement Learning, +More!

Udemy Link - https://www.udemy.com/course/deep-learning-tensorflow-2/

Please seed as much as you can!

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