Book description
Get to grips with the essentials of deep learning by leveraging the power of Python
About This Book
 Your onestop solution to get started with the essentials of deep learning and neural network modeling
 Train different kinds of neural networks to tackle various problems in Natural Language Processing, computer vision, speech recognition, and more
 Covers popular Python libraries such as Tensorflow, Keras, and more, along with tips on training, deploying and optimizing your deep learning models in the best possible manner
Who This Book Is For
Aspiring data scientists and machine learning experts who have limited or no exposure to deep learning will find this book to be very useful. If you are looking for a resource that gets you up and running with the fundamentals of deep learning and neural networks, this book is for you. As the models in the book are trained using the popular Pythonbased libraries such as Tensorflow and Keras, it would be useful to have sound programming knowledge of Python.
What You Will Learn
 Get to grips with the core concepts of deep learning and neural networks
 Set up deep learning library such as TensorFlow
 Finetune your deep learning models for NLP and Computer Vision applications
 Unify different information sources, such as images, text, and speech through deep learning
 Optimize and finetune your deep learning models for better performance
 Train a deep reinforcement learning model that plays a game better than humans
 Learn how to make your models get the best out of your GPU or CPU
In Detail
Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master.
This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as Convolutional Neural Network, Recurrent Neural Network, and will see some of their applications in realworld domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing. Popular Python library such as TensorFlow is used in this book to build the models. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, small datasets, and more.
This book does not assume any prior knowledge of deep learning. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications.
Style and approach
This stepbystep guide is filled with realworld practical examples and use cases to solve various deep learning problems.
Publisher resources
Table of contents
 Preface
 Why Deep Learning?
 Getting Yourself Ready for Deep Learning
 Getting Started with Neural Networks
 Deep Learning in Computer Vision

NLP  Vector Representation
 Traditional NLP

Deep learning NLP
 Motivation and distributed representation
 Word embeddings
 Word2Vec
 Understanding GloVe
 FastText
 Applications
 Summary
 Advanced Natural Language Processing
 Multimodality
 Deep Reinforcement Learning
 Deep Learning Hacks
 Deep Learning Trends
 Other Books You May Enjoy
Product information
 Title: Deep Learning Essentials
 Author(s):
 Release date: January 2018
 Publisher(s): Packt Publishing
 ISBN: 9781785880360
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