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Practical Data Analysis

You're reading from Practical Data Analysis Pandas, MongoDB, Apache Spark, and more

Product type Paperback

Published in Sep 2016

Publisher

ISBN-13 9781785289712

Length 338 pages

Edition 2nd Edition

Languages

Python

Tools

Apache Spark

Concepts

Data Analysis

Authors (2):

Hector Cuesta

Dr. Sampath Kumar

View More author details

Table of Contents (16) Chapters

Preface

1. Getting Started

2. Preprocessing Data FREE CHAPTER

3. Getting to Grips with Visualization

4. Text Classification

5. Similarity-Based Image Retrieval

6. Simulation of Stock Prices

7. Predicting Gold Prices

8. Working with Support Vector Machines

9. Modeling Infectious Diseases with Cellular Automata

10. Working with Social Graphs

11. Working with Twitter Data

12. Data Processing and Aggregation with MongoDB

13. Working with MapReduce

14. Online Data Analysis with Jupyter and Wakari

15. Understanding Data Processing using Apache Spark

Preface

Practical Data Analysis provides a series of practical projects in order to turn data into insight. It covers a wide range of data analysis tools and algorithms for classification, clustering, visualization, simulation and forecasting. The goal of this book is to help you to understand your data to find patterns, trends, relationships and insight.

This book contains practical projects that take advantage of the MongoDB, D3.js, Python language and its ecosystem to present the concepts using code snippets and detailed descriptions.

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Authors (2)

Dr. Sampath Kumar

Dr. Sampath Kumar

Dr. Sampath Kumar works as an assistant professor and head of Department of Applied Statistics at Telangana University. He has completed M.Sc., M.Phl., and Ph. D. in statistics. He has five years of teaching experience for PG course. He has more than four years of experience in the corporate sector. His expertise is in statistical data analysis using SPSS, SAS, R, Minitab, MATLAB, and so on. He is an advanced programmer in SAS and matlab software. He has teaching experience in different, applied and pure statistics subjects such as forecasting models, applied regression analysis, multivariate data analysis, operations research, and so on for M.Sc. students. He is currently supervising Ph.D. scholars.

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Cuesta

Cuesta

Hector Cuesta is founder and Chief Data Scientist at Dataxios, a machine intelligence research company. Holds a BA in Informatics and a M.Sc. in Computer Science. He provides consulting services for data-driven product design with experience in a variety of industries including financial services, retail, fintech, e-learning and Human Resources. He is an enthusiast of Robotics in his spare time. You can follow him on Twitter at https://twitter.com/hmCuesta.

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