Deep Learning Essentials: Your hands-on guide to the fundamentals of deep learning and neural network modeling

Deep Learning Essentials: Your hands-on guide to the fundamentals of deep learning and neural network modeling

Author: Wei Di – Anurag Bhardwaj – Jianing Wei

ISBN-10 书号: 1785880365
ISBN-13 书号: 9781785880360
Release Finelybook 出版日期: 2018-01-30
pages 页数: 284

$34.99


Book Description to Finelybook sorting

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 real-world 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.
Contents
1: WHY DEEP LEARNING?
2: GETTING YOURSELF READY FOR DEEP LEARNING
3: GETTING STARTED WITH NEURAL NETWORKS
4: DEEP LEARNING IN COMPUTER VISION
5: NLP – VECTOR REPRESENTATION
6: ADVANCED NATURAL LANGUAGE PROCESSING
7: MULTIMODALITY
8: DEEP REINFORCEMENT LEARNING
9: DEEP LEARNING HACKS
10: DEEP LEARNING TRENDS
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
Fine-tune 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 fine-tune 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
Authors
Wei Di
Wei Di is a data scientist with years of experience in machine learning and artificial intelligence. She is passionate about creating smart and scalable intelligent solutions that can impact millions of individuals and empower successful business. Currently, she works a staff data scientist in LinkedIn. She was previously associated with eBay Human Language Technology team and eBay Research Labs. Prior to that, she was with ancestry, working on large-scale data mining in the areas of record linkage. She received her PhD from Purdue University in 2011.
Anurag Bhardwaj
Anurag Bhardwaj currently leads data science efforts at Wiser Solutions, where he focuses on structuring large scale eCommerce inventory. He is particularly interested in using machine learning to solve problems on product category classification, product matching and various related problems in eCommerce. Previously, he worked on image understanding at eBay Research Labs. Anurag received his PhD and MS from the State University of New York at Buffalo and holds a BTech in computer engineering from the National Institute of Technology, Kurukshetra, India.

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