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Big Data Analysis with Python

You're reading from Big Data Analysis with Python Combine Spark and Python to unlock the powers of parallel computing and machine learning

Product type Paperback

Published in Apr 2019

Publisher Packt

ISBN-13 9781789955286

Length 276 pages

Edition 1st Edition

Languages

Python

Tools

Combine

Concepts

Big Data

Authors (3):

Marin

Shukla

VK

View More author details

Table of Contents (11) Chapters

About the Book

1. The Python Data Science Stack

2. Coming Soon FREE CHAPTER

3. Coming Soon

4. Coming Soon

5. Coming Soon

6. Coming Soon

7. Coming Soon

8. Coming Soon

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10. Coming Soon

Approach

Big Data Analysis with Python takes a hands-on approach to understanding how to use Python and Spark to process data and make something useful out of it. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context.

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Authors (3)

Marin

Marin

Ivan Marin is a systems architect and data scientist working at Daitan Group, a Campinas-based software company. He designs big data systems for large volumes of data and implements machine learning pipelines end to end using Python and Spark. He is also an active organizer of data science, machine learning, and Python in So Paulo, and has given Python for data science courses at university level.

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Shukla

Shukla

Ankit Shukla is a data scientist working with World Wide Technology, a leading US-based technology solution provider, where he develops and deploys machine learning and artificial intelligence solutions to solve business problems and create actual dollar value for clients. He is also part of the company's R&D initiative, which is responsible for producing intellectual property, building capabilities in new areas, and publishing cutting-edge research in corporate white papers. Besides tinkering with AI/ML models, he likes to read and is a big-time foodie.

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VK

VK

Sarang VK is a lead data scientist at StraitsBridge Advisors, where his responsibilities include requirement gathering, solutioning, development, and productization of scalable machine learning, artificial intelligence, and analytical solutions using open source technologies. Alongside this, he supports pre-sales and competency.

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