Data Science Kit

Data Science Starter Kit

The Tools You Need to Get Started with Data

From basic statistics to complex modeling and large-scale analytics, the Data Science Starter Kit outlines a clear path to mastering data and gets you started with essential tools, key algorithms and methods, and a survey of the hottest languages and frameworks in today's ecosystem. If you're ready to plunge into the world of data, the Starter Kit provides the comprehensive introduction you're looking for.

Buy any two titles and get the 3rd Free with discount code: OPC10

Or, get them all for $209.20 (60% savings)

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Data Science for Business

Data Science for Business: Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles.

Ebook: $33.99

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Doing Data Science

Doing Data Science: Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in such a wide-ranging, interdisciplinary field? This insightful book, based on Columbia University's Introduction to Data Science class, tells you what you need to know as data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use.

Ebook: $38.99

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Data Science from Scratch

Data Science from Scratch: Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they're also a good way to dive into the discipline without actually understanding it. In this book, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get the hacking skills you need to get started as a data scientist.

Ebook: $33.99

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Field Guide to Hadoop

Field Guide to Hadoop: If your organization is about to enter the world of big data, you not only need to decide whether Apache Hadoop is the right platform to use, but also which of its many components are best suited to your task. This field guide makes the exercise manageable by breaking down the Hadoop ecosystem into short, digestible sections. You'll quickly understand how Hadoop's projects, subprojects, and related technologies work together.

Ebook: $33.99

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Hadoop Fundamentals for Data Scientists

Hadoop Fundamentals for Data Scientists: Get a practical introduction to Hadoop, the framework that made big data and large-scale analytics possible by combining distributed computing techniques with distributed storage. In this video tutorial, hosts Benjamin Bengfort and Jenny Kim discuss the core concepts behind distributed computing and big data, and then show you how to work with a Hadoop cluster and program analytical jobs. You'll also learn how to use higher-level tools such as Hive and Spark.

Video: $119.99

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Introduction to Data Science with R

Introduction to Data Science with R: Learn practical skills for visualizing, transforming, and modeling data in R. This comprehensive video course shows you how to explore and understand data, as well as how to build linear and non-linear models in the R language and environment. It's ideal whether you're a non-programmer with no data science experience, or a data scientist switching to R from other software such as SAS or Excel.

Video: $159.99

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Learning Spark

Learning Spark: Data in all domains is getting bigger. How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates.

Ebook: $33.99

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Python for Data Analysis

Python for Data Analysis: This title is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems.

Ebook: $33.99

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Data Science at the Command Line

Data Science at the Command Line: This hands-on guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You'll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data. To get you started—whether you're on Windows, OS X, or Linux—author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.

Ebook: $33.99

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