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001 From TensorFlow 1.x to TensorFlow 2.0.mp4
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001 From TensorFlow 1.x to TensorFlow 2.0_en.vtt
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001 Plan of Attack.mp4
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001 Plan of Attack_en.vtt
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001 Project Setup & Data Preprocessing.mp4
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001 Project Setup & Data Preprocessing_en.vtt
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001 Project Setup.mp4
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001 Project Setup_en.vtt
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001 SPECIAL COVID-19 BONUS.html
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001 Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit.mp4
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146.3 MB
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001 Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit_en.vtt
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001 What is Reinforcement Learning.mp4
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001 What is Reinforcement Learning_en.vtt
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001 What is Transfer Learning.mp4
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001 What is Transfer Learning_en.vtt
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001 What is the Distributed Training.mp4
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001 What is the Distributed Training_en.vtt
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001 What is the TensorFlow Lite.mp4
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001 What is the TensorFlow Lite_en.vtt
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001 What is the TensorFlow Serving.mp4
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001 What is the TensorFlow Serving_en.vtt
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002 AI Trader - Step 1.mp4
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002 AI Trader - Step 1_en.vtt
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002 Building the Convolutional Neural Network.mp4
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56.6 MB
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002 Building the Convolutional Neural Network_en.vtt
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002 Building the Recurrent Neural Network.mp4
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002 Building the Recurrent Neural Network_en.vtt
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002 Constants, Variables, Tensors.mp4
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23.1 MB
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002 Constants, Variables, Tensors_en.vtt
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002 Course Curriculum & Colab Toolkit.html
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512 B
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002 Data Preprocessing.mp4
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21.1 MB
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002 Data Preprocessing_en.vtt
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002 Importing project dependencies.mp4
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002 Importing project dependencies_en.vtt
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002 Initial dataset preprocessing.mp4
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002 Initial dataset preprocessing_en.vtt
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002 Loading the pollution dataset.mp4
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002 Loading the pollution dataset_en.vtt
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002 Project Setup.mp4
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002 Project Setup_en.vtt
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002 Project setup.mp4
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002 Project setup_en.vtt
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002 TensorFlow Serving architecture.mp4
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002 TensorFlow Serving architecture_en.vtt
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002 The Bellman Equation.mp4
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002 The Bellman Equation_en.vtt
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002 The Neuron.mp4
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002 The Neuron_en.vtt
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002 What are Convolutional Neural Networks.mp4
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002 What are Convolutional Neural Networks_en.vtt
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002 What are Recurrent Neural Networks.mp4
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002 What are Recurrent Neural Networks_en.vtt
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002 YOUR SPECIAL BONUS.html
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003 AI Trader - Step 2.mp4
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003 AI Trader - Step 2_en.vtt
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003 BONUS 10 advantages of TensorFlow.html
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003 Building the Artificial Neural Network.mp4
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003 Building the Artificial Neural Network_en.vtt
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003 Creating dataset Schema.mp4
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003 Creating dataset Schema_en.vtt
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003 Dataset metadata.mp4
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003 Dataset metadata_en.vtt
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003 Dataset preprocessing.mp4
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003 Dataset preprocessing_en.vtt
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003 FREE LEARNING RESOURCES FOR YOU.html
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003 Loading a pre-trained model.mp4
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003 Loading a pre-trained model_en.vtt
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003 Markov Decision Process (MDP).mp4
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003 Markov Decision Process (MDP)_en.vtt
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003 Operations with Tensors.mp4
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003 Operations with Tensors_en.vtt
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003 Project setup.mp4
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003 Project setup_en.vtt
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003 Step 1 - Convolution.mp4
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003 Step 1 - Convolution_en.vtt
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003 The Activation Function.mp4
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003 The Activation Function_en.vtt
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003 Training and Evaluating the Convolutional Neural Network.mp4
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003 Training and Evaluating the Convolutional Neural Network_en.vtt
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003 Training and Evaluating the Recurrent Neural Network.mp4
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003 Training and Evaluating the Recurrent Neural Network_en.vtt
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003 Vanishing Gradient.mp4
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003 Vanishing Gradient_en.vtt
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004 AI Trader - Step 3.mp4
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004 AI Trader - Step 3_en.vtt
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004 BONUS Learning Path.html
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004 Building a model.mp4
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004 Building a model_en.vtt
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004 Computing test set statistics.mp4
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004 Computing test set statistics_en.vtt
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004 Dataset preprocessing.mp4
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004 Dataset preprocessing_en.vtt
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004 Defining a non-distributed model (normal CNN model).mp4
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004 Defining a non-distributed model (normal CNN model)_en.vtt
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004 Defining the Flask application.mp4
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004 Defining the Flask application_en.vtt
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004 HOMEWORK Convolutional Neural Networks.html
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512 B
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004 How do Neural Networks Work.mp4
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004 How do Neural Networks Work_en.vtt
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004 LSTMs.mp4
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004 LSTMs_en.vtt
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004 Loading the MobileNet V2 model.mp4
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004 Loading the MobileNet V2 model_en.vtt
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004 Preprocessing function.mp4
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004 Preprocessing function_en.vtt
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004 Q-Learning Intuition.mp4
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29.3 MB
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004 Q-Learning Intuition_en.vtt
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004 Step 1 Bis - ReLU Layer.mp4
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004 Step 1 Bis - ReLU Layer_en.vtt
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004 Strings.mp4
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004 Strings_en.vtt
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004 Training the Artificial Neural Network.mp4
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004 Training the Artificial Neural Network_en.vtt
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005 AI Trader - Step 4.mp4
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005 AI Trader - Step 4_en.vtt
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005 Anomaly detection with TensorFlow Data Validation.mp4
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005 Anomaly detection with TensorFlow Data Validation_en.vtt
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005 Creating classify function.mp4
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005 Creating classify function_en.vtt
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005 Dataset preprocessing pipeline.mp4
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005 Defining, training and evaluating a model.mp4
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005 Defining, training and evaluating a model_en.vtt
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005 Evaluating the Artificial Neural Network.mp4
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005 Evaluating the Artificial Neural Network_en.vtt
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005 Freezing the pre-trained model.mp4
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005 Freezing the pre-trained model_en.vtt
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005 HOMEWORK SOLUTION Convolutional Neural Networks.html
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614.4 B
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005 How do Neural Networks Learn.mp4
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005 How do Neural Networks Learn_en.vtt
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005 LSTM Practical Intuition.mp4
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005 LSTM Practical Intuition_en.vtt
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005 Setting up a distributed strategy.mp4
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005 Setting up a distributed strategy_en.vtt
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005 Step 2 - Max Pooling.mp4
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005 Step 2 - Max Pooling_en.vtt
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005 Temporal Difference.mp4
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005 Temporal Difference_en.vtt
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005 Training, evaluating the model.mp4
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005 Training, evaluating the model_en.vtt
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006 AI Trader - Step 5.mp4
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006 AI Trader - Step 5_en.vtt
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006 Adding a custom head to the pre-trained model.mp4
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006 Adding a custom head to the pre-trained model_en.vtt
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006 Deep Q-Learning Intuition - Step 1.mp4
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006 Deep Q-Learning Intuition - Step 1_en.vtt
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006 Defining a distributed model.mp4
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006 Defining a distributed model_en.vtt
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006 Gradient Descent.mp4
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006 Gradient Descent_en.vtt
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006 HOMEWORK Artificial Neural Networks.html
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006 LSTM Variations.mp4
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006 LSTM Variations_en.vtt
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006 Preparing Schema for production.mp4
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006 Preparing Schema for production_en.vtt
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006 Saving the model for production.mp4
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006 Saving the model for production_en.vtt
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006 Saving the model.mp4
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006 Saving the model_en.vtt
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006 Starting the Flask application.mp4
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006 Starting the Flask application_en.vtt
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006 Step 3 - Flattening.mp4
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006 Step 3 - Flattening_en.vtt
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006 What's next.html
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007 Dataset Loader function.mp4
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007 Dataset Loader function_en.vtt
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007 Deep Q-Learning Intuition - Step 2.mp4
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007 Deep Q-Learning Intuition - Step 2_en.vtt
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007 Defining the transfer learning model.mp4
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007 Defining the transfer learning model_en.vtt
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007 Final evaluation - Speed test normal model vs distributed model.mp4
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007 Final evaluation - Speed test normal model vs distributed model_en.vtt
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007 HOMEWORK SOLUTION Artificial Neural Networks.html
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007 Saving the Schema.mp4
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007 Saving the Schema_en.vtt
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007 Sending API requests over internet to the model.mp4
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007 Sending API requests over internet to the model_en.vtt
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007 Serving the TensorFlow 2.0 Model.mp4
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007 Serving the TensorFlow 2.0 Model_en.vtt
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007 Step 4 - Full Connection.mp4
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007 Step 4 - Full Connection_en.vtt
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007 Stochastic Gradient Descent.mp4
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007 Stochastic Gradient Descent_en.vtt
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007 TensorFlow Lite Converter.mp4
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007 TensorFlow Lite Converter_en.vtt
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008 Backpropagation.mp4
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008 Backpropagation_en.vtt
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008 Compiling the Transfer Learning model.mp4
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008 Compiling the Transfer Learning model_en.vtt
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008 Converting the model to a TensorFlow Lite model.mp4
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008 Converting the model to a TensorFlow Lite model_en.vtt
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008 Creating a JSON object.mp4
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008 Creating a JSON object_en.vtt
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008 Experience Replay.mp4
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008 Experience Replay_en.vtt
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008 State creator function.mp4
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008 State creator function_en.vtt
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008 Summary.mp4
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008 Summary_en.vtt
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008 What's next.html
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009 Action Selection Policies.mp4
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009 Action Selection Policies_en.vtt
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009 Image Data Generators.mp4
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15.4 MB
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009 Image Data Generators_en.vtt
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009 Loading the dataset.mp4
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009 Loading the dataset_en.vtt
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009 Saving the converted model.mp4
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3.5 MB
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009 Saving the converted model_en.vtt
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009 Sending the first POST request to the model.mp4
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009 Sending the first POST request to the model_en.vtt
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009 Softmax & Cross-Entropy.mp4
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51.4 MB
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009 Softmax & Cross-Entropy_en.vtt
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010 Defining the model.mp4
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5.6 MB
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010 Defining the model_en.vtt
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010 Sending the POST request to a specific model.mp4
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4 MB
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010 Sending the POST request to a specific model_en.vtt
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010 Transfer Learning.mp4
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010 Transfer Learning_en.vtt
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010 What's next.html
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011 Evaluating Transfer Learning results.mp4
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011 Evaluating Transfer Learning results_en.vtt
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VTT
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1.6 KB
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011 Training loop - Step 1.mp4
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MP4
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11.7 MB
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011 Training loop - Step 1_en.vtt
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VTT
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6.3 KB
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012 Fine Tuning model definition.mp4
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MP4
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9.4 MB
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012 Fine Tuning model definition_en.vtt
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VTT
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4.1 KB
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012 Training loop - Step 2.mp4
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MP4
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36.1 MB
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012 Training loop - Step 2_en.vtt
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VTT
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8.5 KB
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013 Compiling the Fine Tuning model.mp4
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MP4
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2.5 MB
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013 Compiling the Fine Tuning model_en.vtt
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VTT
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1.3 KB
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014 Fine Tuning.mp4
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MP4
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4.3 MB
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014 Fine Tuning_en.vtt
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VTT
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2.3 KB
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015 Evaluating Fine Tuning results.mp4
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MP4
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3.6 MB
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015 Evaluating Fine Tuning results_en.vtt
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VTT
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1.8 KB
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18573084-pollution-small.csv
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CSV
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72.7 KB
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18573088-pollution-small.csv
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CSV
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72.7 KB
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19265454-Flask-API.zip
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ZIP
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372.4 KB
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[CourseClub.ME].url
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URL
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102.4 B
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[CourseClub.Me].url
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URL
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102.4 B
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[GigaCourse.Com].url
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URL
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0 B
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external-assets-links.txt
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TXT
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102.4 B
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