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Udemy - Tensorflow 2.0: Deep Learning And Artificial Intelligence [GC]

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Udemy - Tensorflow 2.0: Deep Learning And Artificial Intelligence [GC] (Size: 7 GB)
  1. Artificial Neural Networks Section Introduction.mp4 32.5 MB
  1. Artificial Neural Networks Section Introduction.srt 7.9 KB
  1. Deep Reinforcement Learning Section Introduction.mp4 37.8 MB
  1. Deep Reinforcement Learning Section Introduction.srt 8.6 KB
  1. Differences Between Tensorflow 1.x and Tensorflow 2.x.mp4 42.5 MB
  1. Differences Between Tensorflow 1.x and Tensorflow 2.x.srt 12.2 KB
  1. Embeddings.mp4 58 MB
  1. Embeddings.srt 16.2 KB
  1. GAN Theory.mp4 86.5 MB
  1. GAN Theory.srt 20.7 KB
  1. Gradient Descent.mp4 34.9 MB
  1. Gradient Descent.srt 9.8 KB
  1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 166.7 MB
  1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.7 KB
  1. Intro to Google Colab, how to use a GPU or TPU for free.mp4 65.2 MB
  1. Intro to Google Colab, how to use a GPU or TPU for free.srt 14.1 KB
  1. Introduction.mp4 39.2 MB
  1. Introduction.srt 5.7 KB
  1. Links to TF2.0 Notebooks.html 7.8 KB
  1. Mean Squared Error.mp4 37.3 MB
  1. Mean Squared Error.srt 11.2 KB
  1. Recommender Systems with Deep Learning Theory.mp4 68.7 MB
  1. Recommender Systems with Deep Learning Theory.srt 17.4 KB
  1. Reinforcement Learning Stock Trader Introduction.mp4 29.7 MB
  1. Reinforcement Learning Stock Trader Introduction.srt 6.8 KB
  1. Sequence Data.mp4 103.2 MB
  1. Sequence Data.srt 24 KB
  1. Transfer Learning Theory.mp4 55.2 MB
  1. Transfer Learning Theory.srt 10.7 KB
  1. What is Convolution (part 1).mp4 83.6 MB
  1. What is Convolution (part 1).srt 20.1 KB
  1. What is Machine Learning.mp4 73.2 MB
  1. What is Machine Learning.srt 18.4 KB
  1. What is a Web Service (Tensorflow Serving pt 1).mp4 31.6 MB
  1. What is a Web Service (Tensorflow Serving pt 1).srt 7.7 KB
  1. What is the Appendix.mp4 18 MB
  1. What is the Appendix.srt 3.7 KB
  10. BONUS Where to get discount coupons and FREE deep learning material.mp4 37.8 MB
  10. BONUS Where to get discount coupons and FREE deep learning material.srt 7.9 KB
  10. Batch Normalization.mp4 23.5 MB
  10. Batch Normalization.srt 6.5 KB
  10. Epsilon-Greedy.mp4 37.6 MB
  10. Epsilon-Greedy.srt 7.4 KB
  10. GRU and LSTM (pt 2).mp4 53.6 MB
  10. GRU and LSTM (pt 2).srt 14.4 KB
  11. A More Challenging Sequence.mp4 77.7 MB
  11. A More Challenging Sequence.srt 9.6 KB
  11. Improving CIFAR-10 Results.mp4 86.4 MB
  11. Improving CIFAR-10 Results.srt 13.2 KB
  11. Q-Learning.mp4 61.3 MB
  11. Q-Learning.srt 17.9 KB
  12. Deep Q-Learning DQN (pt 1).mp4 55.7 MB
  12. Deep Q-Learning DQN (pt 1).srt 16.4 KB
  12. Demo of the Long Distance Problem.mp4 143.1 MB
  12. Demo of the Long Distance Problem.srt 23.1 KB
  13. Deep Q-Learning DQN (pt 2).mp4 49.2 MB
  13. Deep Q-Learning DQN (pt 2).srt 13.2 KB
  13. RNN for Image Classification (Theory).mp4 31.5 MB
  13. RNN for Image Classification (Theory).srt 6 KB
  14. How to Learn Reinforcement Learning.mp4 37.5 MB
  14. How to Learn Reinforcement Learning.srt 7.6 KB
  14. RNN for Image Classification (Code).mp4 27.4 MB
  14. RNN for Image Classification (Code).srt 4.2 KB
  15. Stock Return Predictions using LSTMs (pt 1).mp4 80 MB
  15. Stock Return Predictions using LSTMs (pt 1).srt 15.7 KB
  16. Stock Return Predictions using LSTMs (pt 2).mp4 38.2 MB
  16. Stock Return Predictions using LSTMs (pt 2).srt 6.5 KB
  17. Stock Return Predictions using LSTMs (pt 3).mp4 76.7 MB
  17. Stock Return Predictions using LSTMs (pt 3).srt 14.4 KB
  2. Binary Cross Entropy.mp4 21.5 MB
  2. Binary Cross Entropy.srt 7.3 KB
  2. Code Preparation (Classification Theory).mp4 68.5 MB
  2. Code Preparation (Classification Theory).srt 20.3 KB
  2. Code Preparation (NLP).mp4 62.9 MB
  2. Code Preparation (NLP).srt 16.8 KB
  2. Constants and Basic Computation.mp4 50.2 MB
  2. Constants and Basic Computation.srt 9.6 KB
  2. Data and Environment.mp4 56 MB
  2. Data and Environment.srt 15.7 KB
  2. Elements of a Reinforcement Learning Problem.mp4 97.8 MB
  2. Elements of a Reinforcement Learning Problem.srt 26.2 KB
  2. Forecasting.mp4 47.2 MB
  2. Forecasting.srt 12.7 KB
  2. Forward Propagation.mp4 49.3 MB
  2. Forward Propagation.srt 12.2 KB
  2. GAN Code.mp4 78.2 MB
  2. GAN Code.srt 14.9 KB
  2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 117.1 MB
  2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 31.6 KB
  2. Outline.mp4 73.7 MB
  2. Outline.srt 17.1 KB
  2. Recommender Systems with Deep Learning Code.mp4 58.8 MB
  2. Recommender Systems with Deep Learning Code.srt 11.7 KB
  2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4 31.5 MB
  2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).srt 7.3 KB
  2. Stochastic Gradient Descent.mp4 25 MB
  2. Stochastic Gradient Descent.srt 5.4 KB
  2. Tensorflow 2.0 in Google Colab.mp4 51.1 MB
  2. Tensorflow 2.0 in Google Colab.srt 9.5 KB
  2. Tensorflow Serving pt 2.mp4 124.5 MB
  2. Tensorflow Serving pt 2.srt 20.4 KB
  2. What is Convolution (part 2).mp4 25.2 MB
  2. What is Convolution (part 2).srt 7.2 KB
  2. Windows-Focused Environment Setup 2018.mp4 194 MB
  2. Windows-Focused Environment Setup 2018.srt 20 KB
  3. Autoregressive Linear Model for Time Series Prediction.mp4 87.7 MB
  3. Autoregressive Linear Model for Time Series Prediction.srt 14.2 KB
  3. Categorical Cross Entropy.mp4 35.4 MB
  3. Categorical Cross Entropy.srt 9.6 KB
  3. Classification Notebook.mp4 66.3 MB
  3. Classification Notebook.srt 9.4 KB
  3. How to Code Yourself (part 1).mp4 82.1 MB
  3. How to Code Yourself (part 1).srt 22.1 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 KB
  3. Large Datasets and Data Generators.mp4 36.6 MB
  3. Large Datasets and Data Generators.srt 8.8 KB
  3. Momentum.mp4 39.4 MB
  3. Momentum.srt 7.8 KB
  3. Replay Buffer.mp4 24.1 MB
  3. Replay Buffer.srt 6.9 KB
  3. States, Actions, Rewards, Policies.mp4 43 MB
  3. States, Actions, Rewards, Policies.srt 11.3 KB
  3. Tensorflow Lite (TFLite).mp4 42.4 MB
  3. Tensorflow Lite (TFLite).srt 11 KB
  3. Text Preprocessing.mp4 36.1 MB
  3. Text Preprocessing.srt 6.2 KB
  3. The Geometrical Picture.mp4 56.5 MB
  3. The Geometrical Picture.srt 11.5 KB
  3. Uploading your own data to Google Colab.mp4 89.1 MB
  3. Uploading your own data to Google Colab.srt 12 KB
  3. Variables and Gradient Tape.mp4 70.6 MB
  3. Variables and Gradient Tape.srt 13.6 KB
  3. What is Convolution (part 3).mp4 27.6 MB
  3. What is Convolution (part 3).srt 8 KB
  3. Where to get the code.mp4 30.5 MB
  3. Where to get the code.srt 7.6 KB
  4. 2 Approaches to Transfer Learning.mp4 20.6 MB
  4. 2 Approaches to Transfer Learning.srt 6 KB
  4. Activation Functions.mp4 92.2 MB
  4. Activation Functions.srt 22.6 KB
  4. Build Your Own Custom Model.mp4 70.2 MB
  4. Build Your Own Custom Model.srt 13.3 KB
  4. Code Preparation (Regression Theory).mp4 31.3 MB
  4. Code Preparation (Regression Theory).srt 9.1 KB
  4. Convolution on Color Images.mp4 77 MB
  4. Convolution on Color Images.srt 20.6 KB
  4. How to Code Yourself (part 2).mp4 56.4 MB
  4. How to Code Yourself (part 2).srt 13 KB
  4. Markov Decision Processes (MDPs).mp4 49 MB
  4. Markov Decision Processes (MDPs).srt 12.7 KB
  4. Program Design and Layout.mp4 29.8 MB
  4. Program Design and Layout.srt 8.6 KB
  4. Proof that the Linear Model Works.mp4 18.3 MB
  4. Proof that the Linear Model Works.srt 4.6 KB
  4. Text Classification with LSTMs.mp4 60.6 MB
  4. Text Classification with LSTMs.srt 9.8 KB
  4. Variable and Adaptive Learning Rates.mp4 38.5 MB
  4. Variable and Adaptive Learning Rates.srt 15.2 KB
  4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4 43.8 MB
  4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.srt 11.5 KB
  4. Why is Google the King of Distributed Computing.mp4 50.8 MB
  4. Why is Google the King of Distributed Computing.srt 11.3 KB
  5. Adam.mp4 42.6 MB
  5. Adam.srt 13.5 KB
  5. CNN Architecture.mp4 90.9 MB
  5. CNN Architecture.srt 27.9 KB
  5. CNNs for Text.mp4 40.9 MB
  5. CNNs for Text.srt 9.6 KB
  5. Code pt 1.mp4 46.8 MB
  5. Code pt 1.srt 7.2 KB
  5. Multiclass Classification.mp4 46.9 MB
  5. Multiclass Classification.srt 11 KB
  5. Proof that using Jupyter Notebook is the same as not using it.mp4 77.9 MB
  5. Proof that using Jupyter Notebook is the same as not using it.srt 14.2 KB
  5. Recurrent Neural Networks.mp4 92 MB
  5. Recurrent Neural Networks.srt 25.6 KB
  5. Regression Notebook.mp4 71.7 MB
  5. Regression Notebook.srt 12.1 KB
  5. The Return.mp4 20.9 MB
  5. The Return.srt 6.3 KB
  5. Training with Distributed Strategies.mp4 50.1 MB
  5. Training with Distributed Strategies.srt 8.5 KB
  5. Transfer Learning Code (pt 1).mp4 66.6 MB
  5. Transfer Learning Code (pt 1).srt 13.8 KB
  6. CNN Code Preparation.mp4 86.3 MB
  6. CNN Code Preparation.srt 19.6 KB
  6. Code pt 2.mp4 83.4 MB
  6. Code pt 2.srt 11.8 KB
  6. How to Represent Images.mp4 80.9 MB
  6. How to Represent Images.srt 15.6 KB
  6. How to Succeed in this Course (Long Version).mp4 38.9 MB
  6. How to Succeed in this Course (Long Version).srt 14.6 KB
  6. RNN Code Preparation.mp4 20.4 MB
  6. RNN Code Preparation.srt 7.1 KB
  6. Text Classification with CNNs.mp4 46.4 MB
  6. Text Classification with CNNs.srt 6.6 KB
  6. The Neuron.mp4 49.4 MB
  6. The Neuron.srt 12.5 KB
  6. Transfer Learning Code (pt 2).mp4 46.1 MB
  6. Transfer Learning Code (pt 2).srt 10.4 KB
  6. Using the TPU.html 1.8 KB
  6. Value Functions and the Bellman Equation.mp4 43.3 MB
  6. Value Functions and the Bellman Equation.srt 12.5 KB
  7. CNN for Fashion MNIST.mp4 51.6 MB
  7. CNN for Fashion MNIST.srt 8 KB
  7. Code Preparation (ANN).mp4 56.2 MB
  7. Code Preparation (ANN).srt 16.3 KB
  7. Code pt 3.mp4 62.3 MB
  7. Code pt 3.srt 7.8 KB
  7. How does a model learn.mp4 55 MB
  7. How does a model learn.srt 14 KB
  7. Is Theano Dead.mp4 44.4 MB
  7. Is Theano Dead.srt 12.6 KB
  7. RNN for Time Series Prediction.mp4 87.2 MB
  7. RNN for Time Series Prediction.srt 11.2 KB
  7. What does it mean to “learn”.mp4 30.3 MB
  7. What does it mean to “learn”.srt 8.9 KB
  8. ANN for Image Classification.mp4 58.4 MB
  8. ANN for Image Classification.srt 9.9 KB
  8. CNN for CIFAR-10.mp4 34.8 MB
  8. CNN for CIFAR-10.srt 5.4 KB
  8. Code pt 4.mp4 59.2 MB
  8. Code pt 4.srt 8.2 KB
  8. Making Predictions.mp4 42 MB
  8. Making Predictions.srt 8 KB
  8. Paying Attention to Shapes.mp4 64.3 MB
  8. Paying Attention to Shapes.srt 9.9 KB
  8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 39 MB
  8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt 12.7 KB
  8. What order should I take your courses in (part 1).mp4 88.1 MB
  8. What order should I take your courses in (part 1).srt 16.1 KB
  9. ANN for Regression.mp4 84 MB
  9. ANN for Regression.srt 12.8 KB
  9. Data Augmentation.mp4 39.2 MB
  9. Data Augmentation.srt 11.2 KB
  9. GRU and LSTM (pt 1).mp4 76.1 MB
  9. GRU and LSTM (pt 1).srt 21.1 KB
  9. Reinforcement Learning Stock Trader Discussion.mp4 18.2 MB
  9. Reinforcement Learning Stock Trader Discussion.srt 4.4 KB
  9. Saving and Loading a Model.mp4 35.3 MB
  9. Saving and Loading a Model.srt 4.9 KB
  9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 52.5 MB
  9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt 14.9 KB
  9. What order should I take your courses in (part 2).mp4 122.6 MB
  9. What order should I take your courses in (part 2).srt 23 KB
  [GigaCourse.com].url 0 B
  ▲ 247 total files

Description


Udemy - Tensorflow 2.0: Deep Learning And Artificial Intelligence

Generating beautiful, photo-realistic images of people and things that never existed (GANs)
Beating world champions in the strategy game Go, and complex video games like CS:GO and Dota 2 (Deep Reinforcement Learning)
Self-driving cars (Computer Vision) Speech recognition (e.g. Siri) and machine translation (Natural Language Processing)
Even creating videos of people doing and saying things they never did (DeepFakes – a potentially nefarious application of deep learning)
Tensorflow is the world’s most popular library for deep learning, and it’s built by Google, whose parent Alphabet recently became the most cash-rich company in the world (just a few days before I wrote this). It is the library of choice for many companies doing AI and machine learning.

For more Udemy Courses: https://gigacourse.com

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