Practical Data Analysis


Plenty of small businesses face big amounts of data but lack the internal skills to support quantitative analysis. Understanding how to harness the power of data analysis using the latest open source technology can lead them to providing better customer service, the visualization of customer needs, or even the ability to obtain fresh insights about the performance of previous products. Practical Data Analysis is a book ideal for home and small business users who want to slice and dice the data they have on hand with minimum hassle. Practical Data Analysis is a hands-on guide to understanding the nature of your data and turn it into insight. It will introduce you to the use of machine learning techniques, social networks analytics, and econometrics to help your clients get insights about the pool of data they have at hand. Performing data preparation and processing over several kinds of data such as text, images, graphs, documents, and time series will also be covered. Practical Data Analysis presents a detailed exploration of the current work in data analysis through self-contained projects. First you will explore the basics of data preparation and transformation through OpenRefine. Then you will get started with exploratory data analysis using the D3js visualization framework. You will also be introduced to some of the machine learning techniques such as, classification, regression, and clusterization through practical projects such as spam classification, predicting gold prices, and finding clusters in your Facebook friends network. You will learn how to solve problems in text classification, simulation, time series forecast, social media, and MapReduce through detailed projects. Finally you will work with large amounts of Twitter data using MapReduce to perform a sentiment analysis implemented in Python and MongoDB. Practical Data Analysis contains a combination of carefully selected algorithms and data scrubbing that enables you to turn your data into insight.
Download free tutorial in PDF (360 pages) created by Hector Cuesta .
Pages : 360
Size :
File type : PDF
Downloads: 95
Created: 2021-05-15
License: Free
Author(s): Hector Cuesta
Practical Data Analysis

Others Data Analysis Tutorials

Others related eBooks about Practical Data Analysis

Free Range VHDL: The No-frills Guide to Writing Powerful Code for Your Digital Implementations

This book is a fundamental guide to develop the skills necessary to write powerful VHDL code. The approach taken by this book is to provide only what you need to know to get up and running quickly in VHDL....

Case Studies in Infrastructure Change Management

Download free course Case Studies in Infrastructure Change Management, pdf file on 40 pages by by Wendy Look, Mark Dallman....

Complete guide to Adobe Photoshop

With this pdf tutorial you will be able to create your own project in Photoshop .You will learn all the basics and create a project from scratch. Free training courses designated for student....

Think Complexity

Download free course Think Complexity, pdf file on 228 pages by Allen Downey....

NGINX Unit Cookbook

Download free course NGINX Unit Cookbook, pdf file on 70 pages by Derek DeJonghe....

Kubernetes for Full-Stack Developers

Whether you're just curious, getting started with Kubernetes, or have experience with it, ..., download free Kubernetes tutorial in PDF (637 pages) created by Hanif Jetha ....

Software Above the Level of a Single Device

Download free course Software Above the Level of a Single Device, pdf file on 18 pages by Tim O'Reilly....

Cloud Native Applications

Cloud computing is a game changer. Being able to automate and constantly adjust infrastruc..., download free Cloud tutorial in PDF (123 pages) created by ....

Think Bayes

If you know how to program with Python and also know a little about probability, you're re..., download free Bayes tutorial in PDF (210 pages) created by ....

An Introduction to Combinatorics and Graph Theory

Combinatorics is a branch of mathematics concerning the study of finite or countable discrete structures. Aspects of combinatorics include counting the structures of a given kind and size (enumerative combinatorics), deciding when certain criteria can be met, and constructing and analyzing objects...