Leverage the power of deep learning and Keras to solve complex computational problemsKey FeaturesRecipes on training and fine-tuning your neural network models efficiently using KerasA highly practical guide to simplify your understanding of neural networks and their implementationThis book is a must-have on your shelf if you are planning to put your deep learning knowledge to practical useBook DescriptionKeras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy.This book shows you how to tackle different problems in training efficient deep learning models using the popular Keras library. Starting with installing and setting up of Keras, the book demonstrates how you can perform deep learning with Keras on top of Tensorflow, Apache MXNet and CNTK backend's. From loading the data to fitting and evaluating your model for optimal performance, you will go through a step by step process to tackle every possible problem in training deep models. You will implement efficient convolutional neural networks, recurrent neural networks, adversarial networks and more, with the help of this handy guide. You will also see how to train these models for real-world image and language processing tasks.By the end of this book, you will have a practical, hands-on understanding of how you can leverage the power of Python and Keras to perform effective deep learning.What you will learnInstall and configure Keras on top of Tensorflow, Apache MXNet and CNTKDevelop a strong background in neural network programming using the Keras libraryUnderstand the details of different Keras layers like Core, Embedding and so onUse Keras to implement simple feed-forward neural networks and the more complex CNNs, RNNsWork with various datasets, models used for image and text classificationDevelop text summarization and Reinforcement Learning models using KerasWho This Book Is ForData scientists and machine learning experts looking to find practical solutions to the common problems encountered while training deep learning models will find this book to be a useful resource. A basic understanding of Python, as well as some experience with machine learning and neural networks is required for this book.
Author: Rajdeep Dua