You're reading from Python Data Mining Quick Start Guide

Product typeBook

Published inApr 2019

Reading LevelBeginner

PublisherPackt

ISBN-139781789800265

Edition1st Edition

Languages

Python

Concepts

Data Mining

Author (1)

Nathan Greeneltch

Summary

This chapter introduced the contents of the book and covered getting started with your software environment. It also covered how to get high-speed Python and popular libraries such as pandas, scikit-learn, and seaborn. After reading this chapter and setting your environment, you should be ready to follow along with the demonstrations throughout the rest of the book.

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Python Data Mining Quick Start Guide

Published in: Apr 2019Publisher: PacktISBN-13: 9781789800265

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Author (1)

Nathan Greeneltch

Nathan Greeneltch, PhD is a ML engineer at Intel Corp and resident data mining and analytics expert in the AI consulting group. Hes worked with Python analytics in both the start-up realm and the large-scale manufacturing sector over the course of the last decade. Nathan regularly mentors new hires and engineers fresh to the field of analytics, with impromptu chalk talks and division-wide knowledge-sharing sessions at Intel. In his past life, he was a physical chemist studying surface enhancement of the vibration signals of small molecules; a topic on which he wrote a doctoral thesis while at Northwestern University in Evanston, IL. Nathan hails from the southeastern United States, with family in equal parts from Arkansas and Florida
Read more about Nathan Greeneltch

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