Hands-On Deep Learning Architectures with Python
This book explains the essential learning algorithms used for deep and shallow architectures. Packed with practical implementations to help you understand the concepts and ideas required to build efficient artificial intelligence systems, this book will help you construct deep models using popular frameworks and datasets.
Offered by
Difficulty Level
Intermediate
Completion Time
10h32m
Language
English
About Book
Who Is This Book For?
If you’re a data scientist, machine learning developer/engineer, or deep learning practitioner, or are curious about AI and want to upgrade your knowledge of various deep learning architectures, this book will appeal to you. You are expected to have some knowledge of statistics and machine learning algorithms to get the best out of this book
Hands-On Deep Learning Architectures with Python
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 10h32m total length
Getting Started with Deep Learning
Deep Feedforward Networks
Restricted Boltzmann Machines and Autoencoders
CNN Architecture
Mobile Neural Networks and CNNs
Recurrent Neural Networks
Generative Adversarial Networks
New Trends of Deep Learning
Related Resources
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