01 – Introduction
001 Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit00:00:00
02 – TensorFlow 2.0 Basics
001 From TensorFlow 1.x to TensorFlow 2.000:00:00
002 Constants, Variables, Tensors00:00:00
003 Operations with Tensors00:00:00
004 Strings00:00:00
03 – Artificial Neural Networks
001 Project Setup00:00:00
002 Data Preprocessing00:00:00
003 Building the Artificial Neural Network00:00:00
004 Training the Artificial Neural Network00:00:00
005 Evaluating the Artificial Neural Network00:00:00
04 – Convolutional Neural Networks
001 Project Setup & Data Preprocessing00:00:00
002 Building the Convolutional Neural Network00:00:00
003 Training and Evaluating the Convolutional Neural Network00:00:00
05 – Recurrent Neural Networks
001 Project Setup & Data Preprocessing00:00:00
002 Building the Recurrent Neural Network00:00:00
003 Training and Evaluating the Recurrent Neural Network00:00:00
06 – Transfer Learning and Fine Tuning
001 What is Transfer Learning00:00:00
002 Project Setup00:00:00
003 Dataset preprocessing00:00:00
004 Loading the MobileNet V2 model00:00:00
005 Freezing the pre-trained model00:00:00
006 Adding a custom head to the pre-trained model00:00:00
007 Defining the transfer learning model00:00:00
008 Compiling the Transfer Learning model00:00:00
009 Image Data Generators00:00:00
010 Transfer Learning00:00:00
011 Evaluating Transfer Learning results00:00:00
012 Fine Tuning model definition00:00:00
013 Compiling the Fine Tuning model00:00:00
014 Fine Tuning00:00:00
07 – Deep Reinforcement Learning Theory
001 What is Reinforcement Learning00:00:00
002 The Bellman Equation00:00:00
003 Markov Decision Process (MDP)00:00:00
08 – Deep Reinforcement Learning for Stock Market trading
09 – Data Validation with TensorFlow Data Validation (TFDV)
10 – Dataset Preprocessing with TensorFlow Transform (TFT)
11 – Fashion API with Flask and TensorFlow 2.0
12 – Image Classification API with TensorFlow Serving
13 – TensorFlow Lite Prepare a model for a mobile device
14 – Distributed Training with TensorFlow 2.0
15 – Annex 1 – Artificial Neural Networks Theory
16 – Annex 2 – Convolutional Neural Networks Theory
17 – Annex 3 – Recurrent Neural Networks Theory
