A list of free to download eBooks on Analytics, Data Mining and Big Data

Ivy Apr 26, 2015 No Comments

The Complete Guide to Facebook Analytics

This is a great book to start with understanding how metrics are used for branding, using the success story of Facebook.

Blueprint for Success: Starting a Business Analyst Career

It gives an insight into the profession of a Business Analyst and walks you through the process of  launching your career in Business Analytics.

Multivariate Data Analysis

This edition is a simple applications-oriented introduction to multivariate analysis, for the non-statistician.

Data Structures and Algorithms

The book covers the fundamentals of data structure and algorithms design.

Theory and Applications for Advanced Text Mining

This is an introductory book to advanced text mining techniques.

No More Secrets with Big Data Analytics 

This book provides an overview of Big Data reality and how to unlock its potential.

Medical Statistics: A Guide to SPSS, Data Analysis and Critical Appraisal

A useful resource of statistical tools meant for researchers.

Data Warehousing and Data Mining 

The book is an introduction to data warehousing and data mining.

Modeling With Data

It explains how to execute computationally intensive analyses on very large data sets, create and debug statistical models, and how to run an analysis and check the results.

Data Mining and Analysis – Fundamental Concepts and Algorithms

The book lays the foundations of data mining and analysis, integrating related concepts from machine learning and statistics with an algorithmic perspective. It makes use of examples, covers core methods and cutting-edge research.

An Introduction to inbound Marketing Analytics

This highlights important inbound marketing metrics for data-driven decision making, for optimised marketing. It also tells you how to analyse the most important marketing channels.

The eBook explores data analytics and social business in the context of Big Data.

Gaussian Processes for Machine Learning

It describes the mathematical foundations and practical application of Gaussian processes, and how to apply Gaussian process methods to solve a range of problems.