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.

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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.

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 tells you what you need to know.

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 data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.

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.

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.

Introduction to Data Science with R

Introduction to Data Science with 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.

Learning Spark

Learning Spark: Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You’ll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning.

Python for Data Analysis

Python for Data Analysis: 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. This book is not an exposition on analytical methods using Python as the implementation language.

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.

Strata + Hadoop World

San Jose · London · Beijing · New York · Singapore

Tap into the collective intelligence of the leading minds in data—decision makers using the power of big data to drive business strategy, and practioners who collect, analyze, and manipulate data. Strata gives you the skills, tools, and technologies you need to make data work today—and the insights and visionary thinking O'Reilly is known for.

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