A Complete Guide on TensorFlow 2.0 using Keras API-2022

About Course

Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0

Categories Development

Course Curriculum

01 – Introduction

001 Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit

00:00

02 – TensorFlow 2.0 Basics

03 – Artificial Neural Networks

04 – Convolutional Neural Networks

05 – Recurrent Neural Networks

06 – Transfer Learning and Fine Tuning

001 What is Transfer Learning

00:00
002 Project Setup

00:00
003 Dataset preprocessing

00:00
004 Loading the MobileNet V2 model

00:00
005 Freezing the pre-trained model

00:00
006 Adding a custom head to the pre-trained model

00:00
007 Defining the transfer learning model

00:00
008 Compiling the Transfer Learning model

00:00
009 Image Data Generators

00:00
010 Transfer Learning

00:00
011 Evaluating Transfer Learning results

00:00
012 Fine Tuning model definition

00:00
013 Compiling the Fine Tuning model

00:00
014 Fine Tuning

00:00

07 – Deep Reinforcement Learning Theory

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

€90.99

Course Details

Level: All Levels

Duration: 0

Enrolled:0

Last Updated:February 7, 2022

A Complete Guide on TensorFlow 2.0 using Keras API-2022

About Course

Course Curriculum

01 – Introduction

001 Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit

02 – TensorFlow 2.0 Basics

001 From TensorFlow 1.x to TensorFlow 2.0

002 Constants, Variables, Tensors

003 Operations with Tensors

004 Strings

03 – Artificial Neural Networks

001 Project Setup

002 Data Preprocessing

003 Building the Artificial Neural Network

004 Training the Artificial Neural Network

005 Evaluating the Artificial Neural Network

04 – Convolutional Neural Networks

001 Project Setup & Data Preprocessing

002 Building the Convolutional Neural Network

003 Training and Evaluating the Convolutional Neural Network

05 – Recurrent Neural Networks

001 Project Setup & Data Preprocessing

002 Building the Recurrent Neural Network

003 Training and Evaluating the Recurrent Neural Network

06 – Transfer Learning and Fine Tuning

001 What is Transfer Learning

002 Project Setup

003 Dataset preprocessing

004 Loading the MobileNet V2 model

005 Freezing the pre-trained model

006 Adding a custom head to the pre-trained model

007 Defining the transfer learning model

008 Compiling the Transfer Learning model

009 Image Data Generators

010 Transfer Learning

011 Evaluating Transfer Learning results

012 Fine Tuning model definition

013 Compiling the Fine Tuning model

014 Fine Tuning

07 – Deep Reinforcement Learning Theory

001 What is Reinforcement Learning

002 The Bellman Equation

003 Markov Decision Process (MDP)

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

Course Details

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