Niloy Purkait - Hands-On Neural Networks with Keras: Design and create neural networks using deep learning and artificial intelligence principles
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Copyright 2019 Packt Publishing
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Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
Commissioning Editor: Sunith Shetty
Acquisition Editor: Devika Battike
Content Development Editor: Unnati Guha
Technical Editor: Sayli Nikalje
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Indexer: Rekha Nair
Graphics: Jisha Chirayil
Production Coordinator: Jyoti Chauhan
First published: March 2019
Production reference: 1300319
Published by Packt Publishing Ltd.
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B3 2PB, UK.
ISBN 978-1-78953-608-9
www.packtpub.com
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Niloy Purkait is a technology and strategy consultant by profession. He currently resides in the Netherlands, where he offers his consulting services to local and international companies alike. He specializes in integrated solutions involving artificial intelligence, and takes pride in navigating his clients through dynamic and disruptive business environments.
He has a masters in Strategic Management from Tilburg University, and a full specialization in data science from Michigan University. He has advanced industry grade certifications from IBM, in subjects like signal processing, cloud computing, machine and deep learning. He is also perusing advanced academic degrees in several related fields, and is a self-proclaimed lifelong learner.
Mayur Ravindra Narkhede has a good blend of experience in data science and the industrial domain. He is a researcher with a B.Tech in computer science and an M.Tech in computer science and engineering, with a specialization in artificial intelligence.
A data scientist whose core experience lies in building automated end-to-end solutions, he is proficient at applying technology, artificial intelligence, machine learning, data mining, and design-thinking to help identify and achieve avenues for business growth.
He has worked on multiple advanced solutions, including ones to do with machine learning and predictive model development for the oil and gas industry, financial services, road traffic and transport, and life sciences; and big data platforms for asset-intensive industries.
, Overview of Neural Networks , describes how to think intuitively about the fundamental nature, structure, and different forms of data. You will learn how to deal with basic data types, advanced data structures (image, video, audio, text, sensor, and multimedia data), and learn the underlying abstractions of extracting information from these varying data structures.
, A Deeper Dive into Neural Networks, takes an in-depth look at the mathematical background of neural networks. Then, you will explore how being a Keras user can make you more productive and outperform the competition, by means of rapid development cycles that iteratively improve your machine learning project outcomes.
, Signal Processing - Data Analysis with Neural Networks, covers how to become familiarized with the necessary types of transformations and normalizations essential to make neural networks work well with complete hands-on examples.
, Convolutional Neural Networks, provides an overview of different types of convolutional and pooling layers that may be used in neural networks used to process sensory input from images on your laptop to databases and real-time Internet of Things (IoT) applications. You will then gain information about processing pipelines associated with CNNs, and experiment with the latest object detection APIs and models available.
, Recurrent Neural Networks , focuses deeper on the theory behind different types of recurrent networks and what it means to be a Turing-complete algorithm.
, Long Short-Term Memory Networks , helps you to explore in detail a specific type of RNN known as LSTM networks, and understand yet another neural network architecture that was inspired by our own biology.
, Reinforcement Learning with Deep Q-Networks
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