Practical Data Science
A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets
|Price||$28.98 - $46.82
|Author||Andreas Francois Vermeulen|
|Format||Paper book / ebook (PDF)|
Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets.
The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions.
Become fluent in the essential concepts and terminology of data science and data engineering; Build and use a technology stack that meets industry criteria; Master the methods for retrieving actionable business knowledge; Coordinate the handling of polyglot data types in a data lake for repeatable results.
by Tony Ojeda, Sean Patrick Murphy, Benjamin Bengfort, Abhijit Dasgupta
Starting with the basics, this book will cover how to set up your numerical programming environment, introduce you to the data science pipeline (an iterative process by which data science projects are completed), and guide you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter...
Price: $29.99 | Publisher: Packt Publishing | Release: 2014
by Nina Zumel, John Mount
Business analysts and developers are increasingly collecting, curating, analyzing, and reporting on crucial business data. The R language and its associated tools provide a straightforward way to tackle day-to-day data science tasks without a lot of academic theory or advanced mathematics.Practical Data Science with R shows you how to app...
Price: $21.42 | Publisher: Manning | Release: 2014
by Nina Zumel, John Mount
Practical Data Science with R, Second Edition takes a practice-oriented approach to explaining basic principles in the ever expanding field of data science. You'll jump right to real-world use cases as you apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business inte...
Price: $39.99 | Publisher: Manning | Release: 2019
by Harvinder Atwal
Gain a practical introduction to DataOps, a new discipline for delivering data science at scale inspired by practices at companies such as Facebook, Uber, LinkedIn, Twitter, and eBay. Organizations need more than the latest AI algorithms, hottest tools, and best people to turn data into insight-driven action and useful analytical data pro...
Price: $32.99 | Publisher: Apress | Release: 2020
by Dan Toomey
R is a powerful, open source, functional programming language. It can be used for a wide range of programming tasks and is best suited to produce data and visual analytics through customizable scripts and commands.The purpose of the book is to explore the core topics that data scientists are interested in. This book draws from a wide vari...
Price: $30.99 | Publisher: Packt Publishing | Release: 2014
by Dejan Sarka
SQL Server only started to fully support data science with its two most recent editions. If you are a professional from both worlds, SQL Server and data science, and interested in using SQL Server and Machine Learning (ML) Services for your projects, then this is the ideal book for you.This book is the ideal introduction to data science w...
Price: $34.99 | Publisher: Packt Publishing | Release: 2018
by Alberto Boschetti, Luca Massaron
Fully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries. This book offers up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikit-learn.The book covers detai...
Price: $44.99 | Publisher: Packt Publishing | Release: 2018
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 collect...
Publisher: Manning | Release: 2016