Deep Learning: A Comprehensive Guide

by Shriram K Vasudevan

Deep A Comprehensive Guide provides comprehensive coverage of Deep Learning (DL) and Machine Learning (ML) concepts. DL and ML are the most sought-after domains, requiring a deep understanding – and this book gives no less than that. This book enables the reader to build innovative and useful applications based on ML and DL. Starting with the basics of neural networks, and continuing through the architecture of various types of CNNs, RNNs, LSTM, and more till the end of the book, each and every topic is given the utmost care and shaped professionally and comprehensively.

Key Features



Includes the smooth transition from ML concepts to DL concepts

Line-by-line explanations have been provided for all the coding-based examples

Includes a lot of real-time examples and interview questions that will prepare the reader to take up a job in ML/DL right away

Even a person with a non-computer-science background can benefit from this book by following the theory, examples, case studies, and code snippets

Every chapter starts with the objective and ends with a set of quiz questions to test the reader’s understanding

Includes references to the related YouTube videos that provide additional guidance AI is a domain for everyone. This book is targeted toward everyone irrespective of their field of specialization. Graduates and researchers in deep learning will find this book useful.

290 pages, Kindle Edition

Published December 24, 2021

Reviews

[Rick Sam · Rating 3 out of 5]

An Introduction work for beginners --
This Work, gives examples from tools.

The Author covers from, Tools to Architectures.

This is written for undergraduates.

List of Chapters, that you'd go through,


Machine Learning Fundamentals,
Deep Learning Framework,
Convolutional Neural Network,
Convolutional Neural Network Architectures,
Recurrent Neural Network,
Auto-Encoders,
Generative Models & Transfer Learning


Deus Vult,
Gottfreid