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Practical Data Analysis Cookbook

You're reading from Practical Data Analysis Cookbook Over 60 practical recipes on data exploration and analysis

Product type Paperback

Published in Apr 2016

Publisher

ISBN-13 9781783551668

Length 384 pages

Edition 1st Edition

Languages

Python

Tools

Pandas

Concepts

Data Analysis

Author (1):

Tomasz Drabas

View More author details

Table of Contents (13) Chapters

Preface

1. Preparing the Data FREE CHAPTER

2. Exploring the Data

3. Classification Techniques

4. Clustering Techniques

5. Reducing Dimensions

6. Regression Methods

7. Time Series Techniques

8. Graphs

9. Natural Language Processing

10. Discrete Choice Models

11. Simulations

Index

Chapter 5. Reducing Dimensions

In this chapter, we will cover various techniques to reduce dimensions of your data. You will learn the following recipes:

Creating three-dimensional scatter plots to present principal components
Reducing the dimensions using the kernel version of PCA
Using Principal Component Analysis to find things that matter
Finding the principal components in your data using randomized PCA
Extracting the useful dimensions using Linear Discriminant Analysis
Using various dimension reduction techniques to classify calls using the k-Nearest Neighbors classification model

The rest of the chapter is locked

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Authors (1)

Drabas

Drabas

Tomasz Drabas is a Data Scientist working for Microsoft and currently residing in the Seattle area. He has over 12 years' international experience in data analytics and data science in numerous fields: advanced technology, airlines, telecommunications, finance, and consulting. Tomasz started his career in 2003 with LOT Polish Airlines in Warsaw, Poland while finishing his Master's degree in strategy management. In 2007, he moved to Sydney to pursue a doctoral degree in operations research at the University of New South Wales, School of Aviation; his research crossed boundaries between discrete choice modeling and airline operations research. During his time in Sydney, he worked as a Data Analyst for Beyond Analysis Australia and as a Senior Data Analyst/Data Scientist for Vodafone Hutchison Australia among others. He has also published scientific papers, attended international conferences, and served as a reviewer for scientific journals. In 2015 he relocated to Seattle to begin his work for Microsoft. While there, he has worked on numerous projects involving solving problems in high-dimensional feature space.

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