Introduction to Machine Learning with Python 
by Sarah Guido, Andreas Muller
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.Y...
Price: $32.38 | Publisher: O'Reilly Media | Release: 2016
Sams Teach Yourself Apache Spark in 24 Hours
by Jeffrey Aven
Apache Spark is a fast, scalable, and flexible open source distributed processing engine for big data systems and is one of the most active open source big data projects to date. In just 24 lessons of one hour or less, Sams Teach Yourself Apache Spark in 24 Hours helps you build practical Big Data solutions that leverage Spark's amazing speed, scalability, simplicity, and versatility.This book's s...
Price: $32.51 | Publisher: SAMS Publishing | Release: 2016
by Mohammed Guller
This book is a step-by-step guide for learning how to use Spark for different types of big-data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning. It covers Spark core and its add-on libraries, including Spark SQL, Spark Streaming, GraphX, MLlib, and Spark ML.Big Data Analytics with Spark shows you how to use Spark and leverage its easy-to-use feat...
Price: $29.99 | Publisher: Apress | Release: 2016
Scalable Big Data Architecture 
by Bahaaldine Azarmi
This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance.Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which inv...
Price: $23.50 | Publisher: Apress | Release: 2016
by Jake VanderPlas
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all - IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with ...
Price: $54.31 | Publisher: O'Reilly Media | Release: 2016
FREE EBOOK - Exploring Data Science
by John Mount, Nina Zumel
There's never been a better time to get into data science. But where do you start? Data Science is a broad field, incorporating aspects of statistics, machine learning, and data engineering. It's easy to become overwhelmed, or end up learning about a small section of data science or a single methodology.Exploring Data Science is a collection of five hand-picked chapters introducing you to various ...
Publisher: Manning | Release: 2016
Data Science Essentials in Python
by Dmitry Zinoviev
Data science is one of the fastest-growing disciplines in terms of academic research, student enrollment, and employment. Python, with its flexibility and scalability, is quickly overtaking the R language for data-scientific projects. Keep Python data-science concepts at your fingertips with this modular, quick reference to the tools used to acquire, clean, analyze, and store data.This one-stop solution cov...
Price: $17.90 | Publisher: The Pragmatic Programmers | Release: 2016
Learning Probabilistic Graphical Models in R
by David Bellot
Probabilistic graphical models (PGM, also known as graphical models) are a marriage between probability theory and graph theory. Generally, PGMs use a graph-based representation. Two branches of graphical representations of distributions are commonly used, namely Bayesian networks and Markov networks. R has many packages to implement graphical models.We'll start by showing you how to transform a classi...
Price: $34.99 | Publisher: Packt Publishing | Release: 2016
by Prateek Joshi, David Millan Escriva, Vinicius Godoy
Open CV is a cross-platform, free-for-use library that is primarily used for real-time Computer Vision and image processing. It is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation.Whether you are completely new to the concept of Computer Vision or have a basic understanding of it...
Price: $38.25 | Publisher: Packt Publishing | Release: 2016
by Ivan Idris
Data analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning.Python Data Analysis Cookbook...
Price: $34.99 | Publisher: Packt Publishing | Release: 2016