Hands-On Neural Networks with TensorFlow 2.0
This book is a guide to the TensorFlow (TF) framework, from the static graph architecture of TF 1.x to the eager execution and all the new features introduced in TF 2.0. Neural Networks applications are developed throughout the book with the aim of making the reader capable of developing neural networks-based solutions to real problems using TF 2.0
Offered by
Difficulty Level
Intermediate
Completion Time
11h56m
Language
English
About Book
Who Is This Book For?
If you're a developer who wants to get started with machine learning and TensorFlow, or a data scientist interested in developing neural network solutions in TF 2.0, this book is for you. Experienced machine learning engineers who want to master the new features of the TensorFlow framework will also find this book useful. Basic knowledge of calculus and a strong understanding of Python programming will help you grasp the topics covered in this book.
Hands-On Neural Networks with TensorFlow 2.0
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 11h56m total length
What is Machine Learning?
Neural Networks and Deep Learning
TensorFlow Graph Architecture
TensorFlow 2.0 Architecture
Efficient Data Input Pipelines and Estimator API
Image Classification using TensorFlow Hub
Introduction to Object Detection
Semantic Segmentation and Custom Dataset Builder
Generative Adversarial Networks
Bringing a Model to Production
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