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Deep Learning with R Cookbook

You're reading from   Deep Learning with R Cookbook Over 45 unique recipes to delve into neural network techniques using R 3.5.x

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781789805673
Length 328 pages
Edition 1st Edition
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Authors (3):
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Swarna Gupta Swarna Gupta
Author Profile Icon Swarna Gupta
Swarna Gupta
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Swarna Gupta holds a B.E. in computer science and has 6 years of experience in the data science space. She is currently working with Rolls Royce in the capacity of a data scientist. Her work revolves around leveraging data science and machine learning to create value for the business. She has extensively worked on IoT-based projects in the vehicle telematics and solar manufacturing industries.During her current association with Rolls Royce she worked in various deep learning techniques and solutions to solve fleet issues in aerospace domain. She also manages time from her busy schedule to be a regular pro-bono contributor to social organizations, helping them to solve specific business problems with the help of data science and machine learning.
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Rehan Ali Ansari Rehan Ali Ansari
Author Profile Icon Rehan Ali Ansari
Rehan Ali Ansari
Rehan has a bachelors in Electrical and Electronics engineering with 5 years of experience in data science and machine learning field. He is currently associated with the digital competency at AP Moller Maersk Group in the capacity of a data scientist. He has a diverse background of working in multiple domains like fashion retail, IoT, renewable energy sector and trade finance. He is a strong believer of agile way of developing data driven machine learning and AI products. Out of his busy schedule he manages to explore new areas in the field of AI and robotics.
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Dipayan Sarkar Dipayan Sarkar
Author Profile Icon Dipayan Sarkar
Dipayan Sarkar
Dipayan Sarkar holds a Masters in Economics and comes with 17+ years of experience. Dipayan has won international challenges in predictive modeling and takes a keen interest in the mathematics behind machine learning techniques. Before opting to become an independent consultant and a mentor in the data science and machine learning space with various organizations and educational institutions, he had served in the capacity of a senior data scientist with Fortune 500 companies in the US and Europe. He is currently associated with Great Lakes Institute of Management as a visiting faculty (Analytics) and BML Munjal University as an adjunct faculty (Analytics and Machine Learning). He has co-authored a book on "Ensemble Machine Learning with Python" with PACKT Publishing.
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Table of Contents (11) Chapters Close

Preface 1. Understanding Neural Networks and Deep Neural Networks 2. Working with Convolutional Neural Networks FREE CHAPTER 3. Recurrent Neural Networks in Action 4. Implementing Autoencoders with Keras 5. Deep Generative Models 6. Handling Big Data Using Large-Scale Deep Learning 7. Working with Text and Audio for NLP 8. Deep Learning for Computer Vision 9. Implementing Reinforcement Learning 10. Other Books You May Enjoy

Accelerating with MXNet

MXNet stands for mix and maximize. It is a flexible and scalable deep learning framework that is used to develop and deploy deep learning models. It is capable of running on various heterogeneous systems in a memory-efficient way. MXNet is also supported by various cloud providers such as Amazon Web Services and Microsoft Azure. Developers have the flexibility to go for both imperative and symbolic programming, making it easier for debugging and hyperparameter tuning while maximizing efficiency. Another advantage that MXNet offers is that it supports multiple languages such as Python, R, Scala, Clojure, Julia, Perl, MATLAB, and JavaScript. In this recipe, we will demonstrate how to set up MXNet in Windows and Linux systems.

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Authors (3)

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Profile icon Gupta
Gupta
Rakesh Gupta is best known as an automation champion in the Salesforce ecosystem. He has written over 150 articles on Visual Workflow and Process Builder to show how someone can use Visual Workflow and Process Builder to minimize code usage. He is one of the Visual Workflow and Process Builder experts in the industry. He has trained more than 700 individual professionals around the globe and conducted corporate training. Currently, Rakesh is working as a Salesforce solution architect consultant.
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Ansari
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Rehan has a bachelors in Electrical and Electronics engineering with 5 years of experience in data science and machine learning field. He is currently associated with the digital competency at AP Moller Maersk Group in the capacity of a data scientist. He has a diverse background of working in multiple domains like fashion retail, IoT, renewable energy sector and trade finance. He is a strong believer of agile way of developing data driven machine learning and AI products. Out of his busy schedule he manages to explore new areas in the field of AI and robotics.
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Sarkar
Aurobindo Sarkar leads a team of data scientists and engineers at Session AI, developing cloud-based ML models for in-session marketing in e-commerce and retail. As a former CTO at multiple SaaS startups, he has architected secure, scalable, and highly available AWS cloud applications. His research interests now focus on AWS-based large-scale transformer models for NLP and HFT models for the futures and options market. Aurobindo holds a bachelor's degree in engineering from IIT Delhi, a master's in management from the Indian Institute of Science Bangalore, and a master's in computer science from New York University.
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