| 1. From TensorFlow 1.x to TensorFlow 2.0.mp4 | 114.8 MB | ||
| 1. From TensorFlow 1.x to TensorFlow 2.0.srt | 16.5 KB | ||
| 1. Plan of Attack.mp4 | 10.5 MB | ||
| 1. Plan of Attack.srt | 3.5 KB | ||
| 1. Project Setup & Data Preprocessing.mp4 | 46.4 MB | ||
| 1. Project Setup & Data Preprocessing.srt | 10.2 KB | ||
| 1. Project Setup.mp4 | 22.3 MB | ||
| 1. Project Setup.srt | 4.7 KB | ||
| 1. SPECIAL COVID-19 BONUS.html | 716.8 B | ||
| 1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 | 146.3 MB | ||
| 1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..srt | 26.4 KB | ||
| 1. What is Reinforcement Learning.mp4 | 68.5 MB | ||
| 1. What is Reinforcement Learning.srt | 18.2 KB | ||
| 1. What is Transfer Learning.mp4 | 46.5 MB | ||
| 1. What is Transfer Learning.srt | 6.1 KB | ||
| 1. What is the Distributed Training.mp4 | 11.1 MB | ||
| 1. What is the Distributed Training.srt | 4.3 KB | ||
| 1. What is the TensorFlow Lite.mp4 | 14 MB | ||
| 1. What is the TensorFlow Lite.srt | 5.2 KB | ||
| 1. What is the TensorFlow Serving.mp4 | 24.5 MB | ||
| 1. What is the TensorFlow Serving.srt | 7.6 KB | ||
| 1.1 Flask API.zip | 372.4 KB | ||
| 1.1 Google Colab ANN.html | 102.4 B | ||
| 1.1 Google Colab CNN.html | 102.4 B | ||
| 1.1 Google Colab Deep-Q Trading Bot.html | 102.4 B | ||
| 1.1 Google Colab RNN.html | 102.4 B | ||
| 1.1 Google Colab TFT.html | 102.4 B | ||
| 1.1 Google Colab TensorFlow 1.x to TensorFlow 2.0.html | 102.4 B | ||
| 1.1 pollution_small.csv | 72.7 KB | ||
| 1.2 Google Colab TFDV.html | 102.4 B | ||
| 1.2 pollution_small.csv | 72.7 KB | ||
| 10. Defining the model.mp4 | 11.9 MB | ||
| 10. Defining the model.srt | 3.2 KB | ||
| 10. Sending the POST request to a specific model.mp4 | 9.6 MB | ||
| 10. Sending the POST request to a specific model.srt | 2.4 KB | ||
| 10. Transfer Learning.mp4 | 16.8 MB | ||
| 10. Transfer Learning.srt | 3.1 KB | ||
| 10. What's next.html | 2.2 KB | ||
| 11. Evaluating Transfer Learning results.mp4 | 9.4 MB | ||
| 11. Evaluating Transfer Learning results.srt | 1.6 KB | ||
| 11. Training loop - Step 1.mp4 | 28.1 MB | ||
| 11. Training loop - Step 1.srt | 6.9 KB | ||
| 12. Fine Tuning model definition.mp4 | 24.6 MB | ||
| 12. Fine Tuning model definition.srt | 4.6 KB | ||
| 12. Training loop - Step 2.mp4 | 54.2 MB | ||
| 12. Training loop - Step 2.srt | 9.7 KB | ||
| 13. Compiling the Fine Tuning model.mp4 | 6.4 MB | ||
| 13. Compiling the Fine Tuning model.srt | 1.5 KB | ||
| 14. Fine Tuning.mp4 | 10.2 MB | ||
| 14. Fine Tuning.srt | 2.6 KB | ||
| 15. Evaluating Fine Tuning results.mp4 | 9 MB | ||
| 15. Evaluating Fine Tuning results.srt | 1.9 KB | ||
| 16. Transfer Learning quiz.html | 102.4 B | ||
| 2. AI Trader - Step 1.mp4 | 27.2 MB | ||
| 2. AI Trader - Step 1.srt | 7.8 KB | ||
| 2. Building the Convolutional Neural Network.mp4 | 88.2 MB | ||
| 2. Building the Convolutional Neural Network.srt | 20.2 KB | ||
| 2. Building the Recurrent Neural Network.mp4 | 40 MB | ||
| 2. Building the Recurrent Neural Network.srt | 9.2 KB | ||
| 2. Constants, Variables, Tensors.mp4 | 71.3 MB | ||
| 2. Constants, Variables, Tensors.srt | 13.3 KB | ||
| 2. Course Curriculum & Colab Toolkit.html | 512 B | ||
| 2. Data Preprocessing.mp4 | 61.8 MB | ||
| 2. Data Preprocessing.srt | 10.6 KB | ||
| 2. Importing project dependencies.mp4 | 11.9 MB | ||
| 2. Importing project dependencies.srt | 2.5 KB | ||
| 2. Initial dataset preprocessing.mp4 | 35 MB | ||
| 2. Initial dataset preprocessing.srt | 8.4 KB | ||
| 2. Loading the pollution dataset.mp4 | 24.8 MB | ||
| 2. Loading the pollution dataset.srt | 5 KB | ||
| 2. Project Setup.mp4 | 49.4 MB | ||
| 2. Project Setup.srt | 4.5 KB | ||
| 2. Project setup.mp4 | 8 MB | ||
| 2. Project setup.srt | 2.6 KB | ||
| 2. TensorFlow Serving architecture.mp4 | 19.5 MB | ||
| 2. TensorFlow Serving architecture.srt | 4.5 KB | ||
| 2. The Bellman Equation.mp4 | 95.1 MB | ||
| 2. The Bellman Equation.srt | 31.3 KB | ||
| 2. The Neuron.mp4 | 98.7 MB | ||
| 2. The Neuron.srt | 25 KB | ||
| 2. What are Convolutional Neural Networks.mp4 | 107.9 MB | ||
| 2. What are Convolutional Neural Networks.srt | 22.1 KB | ||
| 2. What are Recurrent Neural Networks.mp4 | 120.9 MB | ||
| 2. What are Recurrent Neural Networks.srt | 24.3 KB | ||
| 2. YOUR SPECIAL BONUS.html | 1.1 KB | ||
| 2.1 Google Colab Distributed Training.html | 102.4 B | ||
| 2.1 Google Colab TensorFlow Lite.html | 102.4 B | ||
| 2.1 Google Colab Transfer Learning and Fine Tuning.html | 102.4 B | ||
| 3. AI Trader - Step 2.mp4 | 11.9 MB | ||
| 3. AI Trader - Step 2.srt | 2.5 KB | ||
| 3. BONUS 10 advantages of TensorFlow.html | 614.4 B | ||
| 3. Building the Artificial Neural Network.mp4 | 60.4 MB | ||
| 3. Building the Artificial Neural Network.srt | 15.2 KB | ||
| 3. Creating dataset Schema.mp4 | 24.1 MB | ||
| 3. Creating dataset Schema.srt | 6.4 KB | ||
| 3. Dataset metadata.mp4 | 20.9 MB | ||
| 3. Dataset metadata.srt | 4.8 KB | ||
| 3. Dataset preprocessing.mp4 | 31.8 MB | ||
| 3. Dataset preprocessing.srt | 6.3 KB | ||
| 3. FREE LEARNING RESOURCES FOR YOU.html | 2.3 KB | ||
| 3. Loading a pre-trained model.mp4 | 20.5 MB | ||
| 3. Loading a pre-trained model.srt | 3.9 KB | ||
| 3. Markov Decision Process (MDP).mp4 | 94.3 MB | ||
| 3. Markov Decision Process (MDP).srt | 27.1 KB | ||
| 3. Operations with Tensors.mp4 | 49.3 MB | ||
| 3. Operations with Tensors.srt | 8.4 KB | ||
| 3. Project setup.mp4 | 25.5 MB | ||
| 3. Project setup.srt | 4.6 KB | ||
| 3. Step 1 - Convolution.mp4 | 97.9 MB | ||
| 3. Step 1 - Convolution.srt | 23.3 KB | ||
| 3. The Activation Function.mp4 | 45.3 MB | ||
| 3. The Activation Function.srt | 12 KB | ||
| 3. Training and Evaluating the Convolutional Neural Network.mp4 | 58.2 MB | ||
| 3. Training and Evaluating the Convolutional Neural Network.srt | 11 KB | ||
| 3. Training and Evaluating the Recurrent Neural Network.mp4 | 48.9 MB | ||
| 3. Training and Evaluating the Recurrent Neural Network.srt | 10.3 KB | ||
| 3. Vanishing Gradient.mp4 | 111 MB | ||
| 3. Vanishing Gradient.srt | 20.5 KB | ||
| 3.1 Google Colab TensorFlow Serving.html | 102.4 B | ||
| 4. AI Trader - Step 3.mp4 | 15.8 MB | ||
| 4. AI Trader - Step 3.srt | 3 KB | ||
| 4. BONUS Learning Path.html | 1.4 KB | ||
| 4. Building a model.mp4 | 14.8 MB | ||
| 4. Building a model.srt | 3.2 KB | ||
| 4. Computing test set statistics.mp4 | 2.5 MB | ||
| 4. Computing test set statistics.srt | 819.2 B | ||
| 4. Convolutional Neural Networks Quiz.html | 102.4 B | ||
| 4. Dataset preprocessing.mp4 | 23.7 MB | ||
| 4. Dataset preprocessing.srt | 5.1 KB | ||
| 4. Defining a non-distributed model (normal CNN model).mp4 | 14 MB | ||
| 4. Defining a non-distributed model (normal CNN model).srt | 3.7 KB | ||
| 4. Defining the Flask application.mp4 | 12.4 MB | ||
| 4. Defining the Flask application.srt | 1.8 KB | ||
| 4. How do Neural Networks Work.mp4 | 81.8 MB | ||
| 4. How do Neural Networks Work.srt | 19 KB | ||
| 4. LSTMs.mp4 | 136.4 MB | ||
| 4. LSTMs.srt | 28.2 KB | ||
| 4. Loading the MobileNet V2 model.mp4 | 17.8 MB | ||
| 4. Loading the MobileNet V2 model.srt | 3.8 KB | ||
| 4. Preprocessing function.mp4 | 21.1 MB | ||
| 4. Preprocessing function.srt | 6 KB | ||
| 4. Q-Learning Intuition.mp4 | 79.1 MB | ||
| 4. Q-Learning Intuition.srt | 21.7 KB | ||
| 4. Recurrent Neural Network Quiz.html | 102.4 B | ||
| 4. Step 1 Bis - ReLU Layer.mp4 | 53.4 MB | ||
| 4. Step 1 Bis - ReLU Layer.srt | 9.7 KB | ||
| 4. Strings.mp4 | 40.2 MB | ||
| 4. Strings.srt | 8.8 KB | ||
| 4. Training the Artificial Neural Network.mp4 | 48.5 MB | ||
| 4. Training the Artificial Neural Network.srt | 10.4 KB | ||
| 5. AI Trader - Step 4.mp4 | 15.9 MB | ||
| 5. AI Trader - Step 4.srt | 3.4 KB | ||
| 5. Anomaly detection with TensorFlow Data Validation.mp4 | 24 MB | ||
| 5. Anomaly detection with TensorFlow Data Validation.srt | 5.4 KB | ||
| 5. Creating classify function.mp4 | 53.1 MB | ||
| 5. Creating classify function.srt | 5.6 KB | ||
| 5. Dataset preprocessing pipeline.mp4 | 74 MB | ||
| 5. Dataset preprocessing pipeline.srt | 10.6 KB | ||
| 5. Defining, training and evaluating a model.mp4 | 23.3 MB | ||
| 5. Defining, training and evaluating a model.srt | 3.4 KB | ||
| 5. Evaluating the Artificial Neural Network.mp4 | 31.4 MB | ||
| 5. Evaluating the Artificial Neural Network.srt | 6.8 KB | ||
| 5. Freezing the pre-trained model.mp4 | 6.1 MB | ||
| 5. Freezing the pre-trained model.srt | 1.7 KB | ||
| 5. HOMEWORK Convolutional Neural Networks.html | 512 B | ||
| 5. How do Neural Networks Learn.mp4 | 112.2 MB | ||
| 5. How do Neural Networks Learn.srt | 19.2 KB | ||
| 5. LSTM Practical Intuition.mp4 | 187.4 MB | ||
| 5. LSTM Practical Intuition.srt | 21 KB | ||
| 5. Setting up a distributed strategy.mp4 | 7.4 MB | ||
| 5. Setting up a distributed strategy.srt | 2.3 KB | ||
| 5. Step 2 - Max Pooling.mp4 | 140.2 MB | ||
| 5. Step 2 - Max Pooling.srt | 21 KB | ||
| 5. Temporal Difference.mp4 | 97.1 MB | ||
| 5. Temporal Difference.srt | 28.8 KB | ||
| 5. Training, evaluating the model.mp4 | 15.2 MB | ||
| 5. Training, evaluating the model.srt | 2.5 KB | ||
| 6. AI Trader - Step 5.mp4 | 33.2 MB | ||
| 6. AI Trader - Step 5.srt | 6.2 KB | ||
| 6. Adding a custom head to the pre-trained model.mp4 | 19.7 MB | ||
| 6. Adding a custom head to the pre-trained model.srt | 4.2 KB | ||
| 6. Artificial Neural Network Quiz.html | 102.4 B | ||
| 6. Deep Q-Learning Intuition - Step 1.mp4 | 99.9 MB | ||
| 6. Deep Q-Learning Intuition - Step 1.srt | 22.4 KB | ||
| 6. Defining a distributed model.mp4 | 12.5 MB | ||
| 6. Defining a distributed model.srt | 2.4 KB | ||
| 6. Gradient Descent.mp4 | 60.6 MB | ||
| 6. Gradient Descent.srt | 14 KB | ||
| 6. HOMEWORK SOLUTION Convolutional Neural Networks.html | 614.4 B | ||
| 6. LSTM Variations.mp4 | 20.1 MB | ||
| 6. LSTM Variations.srt | 4.6 KB | ||
| 6. Preparing Schema for production.mp4 | 19.7 MB | ||
| 6. Preparing Schema for production.srt | 4.3 KB | ||
| 6. Saving the model for production.mp4 | 25.4 MB | ||
| 6. Saving the model for production.srt | 5.3 KB | ||
| 6. Saving the model.mp4 | 9.4 MB | ||
| 6. Saving the model.srt | 2.1 KB | ||
| 6. Starting the Flask application.mp4 | 27.6 MB | ||
| 6. Starting the Flask application.srt | 2.7 KB | ||
| 6. Step 3 - Flattening.mp4 | 7.9 MB | ||
| 6. Step 3 - Flattening.srt | 2.7 KB | ||
| 6. What's next.html | 2.1 KB | ||
| 7. Dataset Loader function.mp4 | 38.9 MB | ||
| 7. Dataset Loader function.srt | 8 KB | ||
| 7. Deep Q-Learning Intuition - Step 2.mp4 | 43.1 MB | ||
| 7. Deep Q-Learning Intuition - Step 2.srt | 9.8 KB | ||
| 7. Defining the transfer learning model.mp4 | 13.2 MB | ||
| 7. Defining the transfer learning model.srt | 2.4 KB | ||
| 7. Final evaluation - Speed test normal model vs distributed model.mp4 | 28.4 MB | ||
| 7. Final evaluation - Speed test normal model vs distributed model.srt | 4.4 KB | ||
| 7. HOMEWORK Artificial Neural Networks.html | 512 B | ||
| 7. Saving the Schema.mp4 | 8.1 MB | ||
| 7. Saving the Schema.srt | 1.8 KB | ||
| 7. Sending API requests over internet to the model.mp4 | 35 MB | ||
| 7. Sending API requests over internet to the model.srt | 4.5 KB | ||
| 7. Serving the TensorFlow 2.0 Model.mp4 | 27.9 MB | ||
| 7. Serving the TensorFlow 2.0 Model.srt | 4.9 KB | ||
| 7. Step 4 - Full Connection.mp4 | 194.1 MB | ||
| 7. Step 4 - Full Connection.srt | 28.6 KB | ||
| 7. Stochastic Gradient Descent.mp4 | 67.2 MB | ||
| 7. Stochastic Gradient Descent.srt | 12.3 KB | ||
| 7. TensorFlow Lite Converter.mp4 | 6.3 MB | ||
| 7. TensorFlow Lite Converter.srt | 1.8 KB | ||
| 8. Backpropagation.mp4 | 43.1 MB | ||
| 8. Backpropagation.srt | 7.3 KB | ||
| 8. Compiling the Transfer Learning model.mp4 | 12.6 MB | ||
| 8. Compiling the Transfer Learning model.srt | 3.5 KB | ||
| 8. Converting the model to a TensorFlow Lite model.mp4 | 4.9 MB | ||
| 8. Converting the model to a TensorFlow Lite model.srt | 1.4 KB | ||
| 8. Creating a JSON object.mp4 | 23.6 MB | ||
| 8. Creating a JSON object.srt | 3.5 KB | ||
| 8. Experience Replay.mp4 | 114.7 MB | ||
| 8. Experience Replay.srt | 23.9 KB | ||
| 8. HOMEWORK SOLUTION Artificial Neural Networks.html | 409.6 B | ||
| 8. State creator function.mp4 | 32.3 MB | ||
| 8. State creator function.srt | 9.6 KB | ||
| 8. Summary.mp4 | 30.3 MB | ||
| 8. Summary.srt | 6 KB | ||
| 8. What's next.html | 2 KB | ||
| 8.1 Yahoo finance - APPLE stocks.html | 102.4 B | ||
| 9. Action Selection Policies.mp4 | 136.9 MB | ||
| 9. Action Selection Policies.srt | 24 KB | ||
| 9. Image Data Generators.mp4 | 32.6 MB | ||
| 9. Image Data Generators.srt | 6.3 KB | ||
| 9. Loading the dataset.mp4 | 10 MB | ||
| 9. Loading the dataset.srt | 1.8 KB | ||
| 9. Saving the converted model.mp4 | 8.7 MB | ||
| 9. Saving the converted model.srt | 1.9 KB | ||
| 9. Sending the first POST request to the model.mp4 | 27.3 MB | ||
| 9. Sending the first POST request to the model.srt | 7.1 KB | ||
| 9. Softmax & Cross-Entropy.mp4 | 117.8 MB | ||
| 9. Softmax & Cross-Entropy.srt | 25.7 KB | ||
| [CourseClub.Me].url | 0 B | ||
| [DesireCourse.Net].url | 0 B | ||
| ▲ 284 total files | |||
A Complete Guide on TensorFlow 2.0 using Keras API
Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0
Created by Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team, Luka Anicin
Last updated 8/2020
English
English [Auto-generated]
For More Courses Visit: https://desirecourse.net
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