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Hands-On Deep Learning Algorithms with Python
Hands-On Deep Learning Algorithms with Python

Hands-On Deep Learning Algorithms with Python: Master deep learning algorithms with extensive math by implementing them using TensorFlow

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Profile Icon Sudharsan Ravichandiran
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₱1989.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.1 (13 Ratings)
Paperback Jul 2019 512 pages 1st Edition
eBook
₱1113.99 ₱1591.99
Paperback
₱1989.99
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Arrow left icon
Profile Icon Sudharsan Ravichandiran
Arrow right icon
₱1989.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.1 (13 Ratings)
Paperback Jul 2019 512 pages 1st Edition
eBook
₱1113.99 ₱1591.99
Paperback
₱1989.99
Subscription
Free Trial
eBook
₱1113.99 ₱1591.99
Paperback
₱1989.99
Subscription
Free Trial

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Hands-On Deep Learning Algorithms with Python

Section 1: Getting Started with Deep Learning

In this section, we will get ourselves familiarized with deep learning and will understand the fundamental deep learning concepts. We will also learn about powerful deep learning framework called TensorFlow, and set TensorFlow up for all of our future deep learning tasks.

The following chapters are included in this section:

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Key benefits

  • Get up to speed with building your own neural networks from scratch
  • Gain insights into the mathematical principles behind deep learning algorithms
  • Implement popular deep learning algorithms such as CNNs, RNNs, and more using TensorFlow

Description

Deep learning is one of the most popular domains in the AI space that allows you to develop multi-layered models of varying complexities. This book introduces you to popular deep learning algorithms—from basic to advanced—and shows you how to implement them from scratch using TensorFlow. Throughout the book, you will gain insights into each algorithm, the mathematical principles involved, and how to implement it in the best possible manner. The book starts by explaining how you can build your own neural networks, followed by introducing you to TensorFlow, the powerful Python-based library for machine learning and deep learning. Moving on, you will get up to speed with gradient descent variants, such as NAG, AMSGrad, AdaDelta, Adam, and Nadam. The book will then provide you with insights into recurrent neural networks (RNNs) and LSTM and how to generate song lyrics with RNN. Next, you will master the math necessary to work with convolutional and capsule networks, widely used for image recognition tasks. You will also learn how machines understand the semantics of words and documents using CBOW, skip-gram, and PV-DM. Finally, you will explore GANs, including InfoGAN and LSGAN, and autoencoders, such as contractive autoencoders and VAE. By the end of this book, you will be equipped with all the skills you need to implement deep learning in your own projects.

Who is this book for?

If you are a machine learning engineer, data scientist, AI developer, or anyone looking to delve into neural networks and deep learning, this book is for you. Those who are completely new to deep learning, but have some experience in machine learning and Python programming will also find the book very helpful.

What you will learn

  • Implement basic-to-advanced deep learning algorithms
  • Master the mathematics behind deep learning algorithms
  • Become familiar with gradient descent and its variants, such as AMSGrad, AdaDelta, Adam, and Nadam
  • Implement recurrent networks, such as RNN, LSTM, GRU, and seq2seq models
  • Understand how machines interpret images using CNN and capsule networks
  • Implement different types of generative adversarial network, such as CGAN, CycleGAN, and StackGAN
  • Explore various types of autoencoder, such as Sparse autoencoders, DAE, CAE, and VAE
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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 25, 2019
Length: 512 pages
Edition : 1st
Language : English
ISBN-13 : 9781789344158
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Product feature icon AI Assistant (beta) to help accelerate your learning
Estimated delivery fee Deliver to Philippines

Standard delivery 10 - 13 business days

₱492.95

Premium delivery 5 - 8 business days

₱2548.95
(Includes tracking information)

Product Details

Publication date : Jul 25, 2019
Length: 512 pages
Edition : 1st
Language : English
ISBN-13 : 9781789344158
Category :
Languages :
Concepts :
Tools :

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Table of Contents

16 Chapters
Section 1: Getting Started with Deep Learning Chevron down icon Chevron up icon
Introduction to Deep Learning Chevron down icon Chevron up icon
Getting to Know TensorFlow Chevron down icon Chevron up icon
Section 2: Fundamental Deep Learning Algorithms Chevron down icon Chevron up icon
Gradient Descent and Its Variants Chevron down icon Chevron up icon
Generating Song Lyrics Using RNN Chevron down icon Chevron up icon
Improvements to the RNN Chevron down icon Chevron up icon
Demystifying Convolutional Networks Chevron down icon Chevron up icon
Learning Text Representations Chevron down icon Chevron up icon
Section 3: Advanced Deep Learning Algorithms Chevron down icon Chevron up icon
Generating Images Using GANs Chevron down icon Chevron up icon
Learning More about GANs Chevron down icon Chevron up icon
Reconstructing Inputs Using Autoencoders Chevron down icon Chevron up icon
Exploring Few-Shot Learning Algorithms Chevron down icon Chevron up icon
Assessments Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.1
(13 Ratings)
5 star 61.5%
4 star 15.4%
3 star 0%
2 star 15.4%
1 star 7.7%
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Surender m Sep 06, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
It’s a great book that’s one should have in their collection. Simple language. Easy to understand with python codes.Great book to start learning.
Amazon Verified review Amazon
Reshma Dec 01, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I completed first chapter. Book so far looks concise, simple and up to the point. I will recommend it to a beginner.
Amazon Verified review Amazon
kalyan reddy k Aug 23, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great material for learning, One should go through this book to get the best out of the Deep learning techniques. Besides theory, one can go through the coding for each technique which helps to understand how things work. GREAT to have one.
Amazon Verified review Amazon
Vikash Jan 01, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Best book for mastering Deep Learning. It will give you in-depth knowledge on Basic to Advance Deep Learning algorithm with mathematics behind each algorithm. Each page made you hungry to go further reading. I recommend it to everyone who wanted to learn Deep Learning from Basic to advance level. Best book ever on Deep Learning.Thanks Sudharsan for writing this amazing book on Deep Learning.
Amazon Verified review Amazon
Amazon Customer Sep 05, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Literally it is the best book on Deep Learning I have ever read. Never have I thought, someone could explain DL in such a simple way that too by making all the complex math very simple. After reading this book, I am literally in love with math.This book is for all sets of audiences. Interested in DL applications? Or wanna learn DL with detailed math or wanna learn DL intuitively? This has covered everything from basic algorithms to advanced algorithms like stack gan, cycle gan, VAE, transformer and more that too with hands-on application.Loved it! Loved it! Loved it! very much.
Amazon Verified review Amazon
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