Artificial Neural Networks with TensorFlow 2: ANN Architecture Machine Learning Projects

✍ Scribed by Poornachandra Sarang

• Publisher: Apress
• Year: 2021
• Tongue: English
• Leaves: 749
• Edition: 1st ed.
• Category: Library

✦ Synopsis

Develop machine learning models across various domains. This book offers a single source that provides comprehensive coverage of the capabilities of TensorFlow 2 through the use of realistic, scenario-based projects.
After learning what's new in TensorFlow 2, you'll dive right into developing machine learning models through applicable projects. This book covers a wide variety of ANN architectures—starting from working with a simple sequential network to advanced CNN, RNN, LSTM, DCGAN, and so on. A full chapter is devoted to each kind of network and each chapter consists of a full project describing the network architecture used, the theory behind that architecture, what data set is used, the pre-processing of data, model training, testing and performance optimizations, and analysis.
This practical approach can either be used from the beginning through to the end or, if you're already familiar with basic ML models, you can dive right into the application that interests you. Line-by-line explanations on major code segments help to fill in the details as you work and the entire project source is available to you online for learning and further experimentation. With Artificial Neural Networks with TensorFlow 2 you'll see just how wide the range of TensorFlow's capabilities are.
What You'll Learn

• Develop Machine Learning Applications
• Translate languages using neural networks
• Compose images with style transfer

Who This Book Is For

Beginners, practitioners, and hard-cored developers who want to master machine and deep learning with TensorFlow 2. The reader should have working concepts of ML basics and terminologies.

✦ Table of Contents

Front Matter ....Pages i-xxix
TensorFlow Jump Start (Poornachandra Sarang)....Pages 1-23
A Closer Look at TensorFlow (Poornachandra Sarang)....Pages 25-70
Deep Dive in tf.keras (Poornachandra Sarang)....Pages 71-132
Transfer Learning (Poornachandra Sarang)....Pages 133-188
Neural Networks for Regression (Poornachandra Sarang)....Pages 189-230
Estimators (Poornachandra Sarang)....Pages 231-290
Text Generation (Poornachandra Sarang)....Pages 291-342
Language Translation (Poornachandra Sarang)....Pages 343-404
Natural Language Understanding (Poornachandra Sarang)....Pages 405-469
Image Captioning (Poornachandra Sarang)....Pages 471-522
Time Series Forecasting (Poornachandra Sarang)....Pages 523-576
Style Transfer (Poornachandra Sarang)....Pages 577-611
Image Generation (Poornachandra Sarang)....Pages 613-669
Image Translation (Poornachandra Sarang)....Pages 671-714
Back Matter ....Pages 715-726

✦ Subjects

Computer Science