cta quote button US

Best Keras Books that You Should Have on Your Bookshelf

In this post, we have prepared a curated top list of reading recommendations for beginners and experienced. This hand-picked list of the best Keras books and tutorials can help fill your brain this April and ensure you’re getting smarter. We have also mentioned the brief introduction of each book based on the relevant Amazon or Reddit descriptions.

1. Deep Learning with Python (2017)

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn’t beat a serious Go player, to defeating a world champion.

Author(s): Francois Chollet

2. Deep Learning with Keras (2017)

This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of hand written digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided.

Author(s): Antonio Gulli, Sujit Pal

3. Reinforcement Learning: With Open AI, TensorFlow and Keras Using Python (2017)

Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You’ll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process.Reinforcement Learning discusses algorithm implementations important for reinforcement learning, including Markov’s Decision process and Semi Markov Decision process. The next section shows you how to get…

Author(s): Abhishek Nandy, Manisha Biswas

4. Deep Learning with Applications Using Python (2018)

Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning.

Author(s): Navin Kumar Manaswi

5. Machine Learning with Python Cookbook: Practical Solutions from Preprocessing (2018)

The Python programming language and its libraries, including pandas and scikit-learn, provide a production-grade environment to help you accomplish a broad range of machine-learning tasks. With this comprehensive cookbook, data scientists and software engineers familiar with Python will benefit from almost 200 practical recipes for building a comprehensive machine-learning pipeline—everything from data preprocessing and feature engineering to model evaluation and deep learning. Learn from author Chris Albon…

Author(s): Chris Albon

6. Deep Learning Cookbook: Practical recipes to get started quickly (2018)

Recent developments in deep learning have put the field center stage for innovation in software engineering. New algorithms and techniques in academia hold promise for many real world problems, and new machine learning platforms are powerful, but aren’t necessarily easy to get started with.With this hands-on cookbook, you’ll discover that deep learning doesn’t need to be intimidating. Aimed at readers who are new to deep learning, this cookbook enables you to solve problems quickly, using the most appropriate platform…

Author(s): Douwe Osinga

7. Deep Learning with Python: A Hands-on Introduction (2017)

Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often acquired by practitioners by reading source code, manuals, and posting questions on community forums, which tends to be a slow and a painful process. Deep Learning with Python allows you …

Author(s): Nikhil Ketkar

8. Mastering TensorFlow 1.x: Advanced machine learning (2018)

Build, scale, and deploy deep neural network models using the star libraries in Python.TensorFlow is the most popular numerical computation library built from the ground up for distributed, cloud, and mobile environments. TensorFlow represents the data as tensors and the computation as graphs.This book is a comprehensive guide that lets you explore the advanced features of TensorFlow 1.x. Gain insight into TensorFlow Core, Keras, TF Estimators, TFLearn, TF Slim…

Author(s): Armando Fandango

9. Practical Convolutional Neural Network Models: Enhance deep learning skills by building intelligent ConvNet models using Keras (2018)

One stop guide to practice ConvNets models from most common to recent advances in artificial intelligence field.Convolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, speech recognition and more. These advances create unprecedented opportunities and challenges to build and deploy large-scale ConvNet applications. This book aims to take you through the building blocks of CNN’s…

Author(s): Pradeep Pujari

You might also be interested in: Socket.io, Sonarqube, YII, Ruby on Rails, WordPress, Shopify, MSSQL, Dojo, Typescript, Javascript Books.

We highly recommend you to buy all paper or e-books in a legal way, for example, on Amazon. But sometimes it might be a need to dig deeper beyond the shiny book cover. Before making a purchase, you can visit resources like Genesis and download some Keras books mentioned below at your own risk. Once again, we do not host any illegal or copyrighted files, but simply give our visitors a choice and hope they will make a wise decision.

Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python

Author(s): Jojo John Moolayil
Publisher: Apress, Year: 2019, Size: 3 Mb, Ext: pdf
ID: 2295774

Python Deep Learning: Exploring deep learning techniques, neural network architectures and GANs with PyTorch, Keras and TensorFlow

Author(s): Ivan Vasilev, Daniel Slater, Gianmario Spacagna, Peter Roelants, Valentino Zocca
Publisher: Packt Publishing, Year: 2019, Size: 24 Mb, Ext: pdf
ID: 2319010

Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python

Author(s): Jojo John Moolayil
Publisher: Apress, Year: 2019, Size: 2 Mb, Ext: epub
ID: 2329579

Reinforcement Learning : With Open AI, TensorFlow and Keras Using Python

Author(s): Abhishek Nandy,Manisha Biswas
Publisher: Apress, Year: 2018, Size: 11 Mb, Ext: pdf
ID: 2178978

Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras

Author(s): Rajalingappaa Shanmugamani
Publisher: Packt Publishing, Year: 2018, Size: 58 Mb, Ext: epub
ID: 2199952

Deep Learning With Keras: Beginner’s Guide To Deep Learning With Keras

Author(s): Frank Millstein
Publisher: CreateSpace Independent Publishing Platform, Year: 2018, Size: 280 Kb, Ext: azw3
ID: 2235712

Deep Learning with Applications Using Python: Chatbots and Face, Object, and Speech Recognition with Tensorflow and Keras

Author(s): Navin Kumar Manaswi
Publisher: Apress, Year: 2018, Size: 11 Mb, Ext: pdf
ID: 2256157

Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

Author(s): Armando Fandango
Publisher: Packt Publishing - ebooks Account, Year: 2018, Size: 15 Mb, Ext: pdf
ID: 2256177

Hands-On Deep Learning for Images with TensorFlow: Build intelligent computer vision applications using TensorFlow and Keras

Author(s): Will Ballard
Publisher: Packt Publishing, Year: 2018, Size: 5 Mb, Ext: epub
ID: 2268569

Hands-On Transfer Learning with Python Implement Advanced Deep Learning and Neural Network Models Using TensorFlow and Keras

Author(s): Dipanjan Sarkar, Raghav Bali, Tamoghna Ghosh
Publisher: Packt Publishing, Year: 2018, Size: 46 Mb, Ext: epub
ID: 2274620

Affiliate Disclaimer: We are a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for us to earn fees by linking to Amazon.com and affiliated sites.

But if you’re going to buy hard covers with at least one eye on the opinions of visiting friends and relatives, these are our choices of the titles you really should have on display. Agree? Disagree? That book’ll knock you on your [rear].” The Crossing, and Cities of the Plain—is the only epic tale of cowboys and the American frontier you need on your bookshelf. It’s a saga that’ll remind you to never take the easy path. This 1968 memoir by writer/pianist/actor Oscar Levant has some of the best quips and comebacks you didn This is the ultimate list of books that every woman over 40 should have on her bookshelf. add them to your TBR list! This is the ultimate list of books that every woman over 40 should have on her bookshelf. If you haven’t them yet, add them to your TBR list! Toggle navigation. To discover more amazing secrets about living your best life From biographies of inspiring innovators to stories that have been must-reads for centuries, these are the top 20 books you should display on your bookshelf. 1 / “The Hitchhiker’s Guide to the Must Have Books In Your Bookshelf There is a big difference between books you want to read and books you want to own! These are must have books everyone needs to collect in their bookshelves.