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
by Zoiner Tejada
Microsoft Azure has over 20 platform-as-a-service (PaaS) offerings that can act in support of a big data analytics solution. So which one is right for your project? This practical book helps you understand the breadth of Azure services by organizing them into a reference framework you can use when crafting your own big data analytics solution.You'll not only be able to determine which service best fits...
Price: $22.99 | Publisher: O'Reilly Media | Release: 2017
Network Security Through Data Analysis, 2nd Edition
by Michael Collins
Traditional intrusion detection and logfile analysis are no longer enough to protect today's complex networks. In the updated second edition of this practical guide, security researcher Michael Collins shows InfoSec personnel the latest techniques and tools for collecting and analyzing network traffic datasets. You'll understand how your network is used, and what actions are necessary to harden an...
Price: $30.58 | 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
by Holden Karau, Rachel Warren
Apache Spark is amazing when everything clicks. But if you haven't seen the performance improvements you expected, or still don't feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your Spark queries run faster and handle larger data sizes, while using fewer resources.Ideal for softw...
Price: $27.31 | Publisher: O'Reilly Media | Release: 2017
by Francois Chollet
Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples.Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-h...
Price: $10.50 | Publisher: Manning | 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
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
F# for Machine Learning Essentials
by Sudipta Mukherjee
The F# functional programming language enables developers to write simple code to solve complex problems. With F#, developers create consistent and predictable programs that are easier to test and reuse, simpler to parallelize, and are less prone to bugs.If you want to learn how to use F# to build machine learning systems, then this is the book you want.Starting with an introduction to the several categorie...
Price: $39.99 | Publisher: Packt Publishing | Release: 2016
Designing Machine Learning Systems with Python
by David Julian
Machine learning is one of the fastest growing trends in modern computing. It has applications in a wide range of fields, including economics, the natural sciences, web development, and business modeling. In order to harness the power of these systems, it is essential that the practitioner develops a solid understanding of the underlying design principles.There are many reasons why machine learning models m...
Price: $34.99 | Publisher: Packt Publishing | Release: 2016