Practical Data Science Cookbook
89 hands-on recipes to help you complete real-world data science projects in R and Python
|Price||$29.99 - $58.44
|Authors||Tony Ojeda, Sean Patrick Murphy, Benjamin Bengfort, Abhijit Dasgupta|
|Format||Paper book / ebook (PDF)|
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, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples in the two most popular programming languages for data analysis - R and Python.
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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...
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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...
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by Dan Toomey
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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
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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