by Russell Jurney
Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they're to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools.Author Ru...
Price: $28.00 | Publisher: O'Reilly Media | Release: 2017
by Brian Godsey
Data collected from customers, scientific measurements, IoT sensors, and so on is valuable only if you understand it. Data scientists revel in the interesting and rewarding challenge of observing, exploring, analyzing, and interpreting this data. Getting started with data science means more than mastering analytic tools and techniques, however; the real magic happens when you begin to think like a data scie...
Price: $30.96 | Publisher: Manning | Release: 2017
FREE EBOOK - The Data Science Design Manual 
by Steven S. Skiena
This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what real...
Price: $61.52 | Publisher: Springer | Release: 2017
by Sivakumaran Raman
If your job involves working with data in any manner, you cannot afford to ignore the R revolution! If your domain is called data analysis, analytics, informatics, data science, reporting, business intelligence, data management, big data, or visualization, you just have to learn R as this programming language is a game-changing sledgehammer.However, if you have looked at a standard text on R or read some of...
Publisher: Self-publishing | Release: 2017
by Rochelle King, Elizabeth Churchill, Caitlin Tan
On the surface, design practices and data science may not seem like obvious partners. But these disciplines actually work toward the same goal, helping designers and product managers understand users so they can craft elegant digital experiences. While data can enhance design, design can bring deeper meaning to data.This practical guide shows you how to conduct data-driven A/B testing for making design deci...
Price: $29.34 | Publisher: O'Reilly Media | Release: 2017
Practical Statistics for Data Scientists 
by Peter Bruce, Andrew Bruce
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many...
Price: $27.49 | Publisher: O'Reilly Media | Release: 2017
Python for Data Analysis, 2nd Edition
by William McKinney
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process.Written by Wes McKinney, the creator...
Price: $24.82 | Publisher: O'Reilly Media | Release: 2017
Advanced Analytics with Spark, 2nd Edition
by Sandy Ryza, Uri Laserson, Josh Wills, Sean Owen
In the second edition of this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. Updated for Spark 2.1, this edition acts as an introduction to these techniques and other best pract...
Price: $29.85 | Publisher: O'Reilly Media | Release: 2017
FREE EBOOK - Exploring the Data Jungle
by Brian Godsey
Some people like to believe that all data is ready to be used immediately. Not so! Data in the wild is hard to track and harder to understand, and the first job of data scientists to identify and prepare data so it can be used. To find your way through the data jungle successfully, you need the right perspective and guidance. (There's no point hacking at overgrowth with a spoon after all!) Identify and...
Publisher: Manning | Release: 2017
by Hadley Wickham, Garrett Grolemund
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.Authors Hadley Wickham and G...
Price: $33.37 | Publisher: O'Reilly Media | Release: 2016