Deep Learning with TensorFlow: Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide

by Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy

Overview

Deep learning is the step that comes after machine learning, and has more advanced
implementations. Machine learning is not just for academics anymore, but is becoming a mainstream practice through wide adoption, and deep learning has taken the front seat. As a data scientist, if you want to explore data abstraction layers, this book will be your guide. This book shows how this can be exploited in the real world with complex raw data using TensorFlow 1.x.

Throughout the book, you’ll learn how to implement deep learning algorithms for machine learning systems and integrate them into your product offerings, including
search, image recognition, and language processing. Additionally, you’ll learn how
to analyze and improve the performance of deep learning models. This can be done by
comparing algorithms against benchmarks, along with machine intelligence, to learn
from the information and determine ideal behaviors within a specific context.

After finishing the book, you will be familiar with machine learning techniques, in particular the use of TensorFlow for deep learning, and will be ready to apply your knowledge to research or commercial projects.

Product Details

ISBN-13:	9781786460127
Publisher:	Packt Publishing
Publication date:	04/24/2017
Sold by:	Barnes & Noble
Format:	eBook
Pages:	320
File size:	7 MB

About the Author

Giancarlo Zaccone has more than ten years of experience in managing research projects both in scientific and industrial areas. He worked as researcher at the C.N.R, the National Research Council, where he was involved in projects relating to parallel computing and scientific visualization. Currently, he is a system and software engineer at a consulting company developing and maintaining software systems for space and defense applications. He is author of the following Packt volumes: Python Parallel Programming Cookbook and Getting Started with TensorFlow.

Md. Rezaul Karim has more than 8 years of experience in the area of research and development with a solid knowledge of algorithms and data structures, focusing C/C++, Java, Scala, R, and Python and big data technologies such as Spark, Kafka, DC/OS, Docker, Mesos, Hadoop, and MapReduce. His research interests include machine learning, deep learning, Semantic Web, big data, and bioinformatics. He is the author of the book titled Large-Scale Machine Learning with Spark, Packt Publishing. He is a Software Engineer and Researcher currently working at the Insight Center for Data Analytics, Ireland. He is also a Ph.D. candidate at the National University of Ireland, Galway. He also holds a BS and an MS degree in Computer Engineering. Before joining the Insight Centre for Data Analytics, he had been working as a Lead Software Engineer with Samsung Electronics, where he worked with the distributed Samsung R&D centers across the world, including Korea, India, Vietnam, Turkey, and Bangladesh. Before that, he worked as a Research Assistant in the Database Lab at Kyung Hee University, Korea. He also worked as an R&D Engineer with BMTech21 Worldwide, Korea. Even before that, he worked as a Software Engineer with i2SoftTechnology, Dhaka, Bangladesh.

Ahmed Menshawy is a Research Engineer at the Trinity College Dublin, Ireland. He has more than 5 years of working experience in the area of Machine Learning and Natural Language Processing (NLP). He holds an MSc in Advanced Computer Science. He started his Career as a Teaching Assistant at the Department of Computer Science, Helwan University, Cairo, Egypt. He taught several advanced ML and NLP courses such as Machine Learning, Image Processing, Linear Algebra, Probability and Statistics, Data structures, Essential Mathematics for Computer Science. Next, he joined as a research scientist at the Industrial research and development lab at IST Networks, based in Egypt. He was involved in implementing the state-of-the-art system for Arabic Text to Speech. Consequently, he was the main machine learning specialist in that company. Later on, he joined the Insight Centre for Data Analytics, the National University of Ireland at Galway as a Research Assistant working on building a Predictive Analytics Platform. Finally, he joined ADAPT Centre, Trinity College Dublin as a Research Engineer. His main role in ADAPT is to build prototypes and applications using ML and NLP techniques based on the research that is done within ADAPT.