Download e-book for kindle: Introducing Data Science: Big Data, Machine Learning and by Davy Cielen, Arno Meysman, Mohamed Ali

By Davy Cielen, Arno Meysman, Mohamed Ali

ISBN-10: 1633430030

ISBN-13: 9781633430037

Summary

Introducing info Science teaches you the way to complete the elemental initiatives that occupy information scientists. utilizing the Python language and customary Python libraries, you will adventure firsthand the demanding situations of facing information at scale and achieve a high-quality beginning in facts science.

Purchase of the print e-book features a loose book in PDF, Kindle, and ePub codecs from Manning Publications.

About the Technology

Many businesses want builders with information technological know-how abilities to paintings on tasks starting from social media advertising and marketing to laptop studying. gaining knowledge of what you want to discover ways to start a occupation as a knowledge scientist can appear bewildering. This e-book is designed that will help you get started.

About the Book

Introducing info ScienceIntroducing information technology explains very important info technological know-how options and teaches you ways to complete the basic initiatives that occupy info scientists. You’ll discover information visualization, graph databases, using NoSQL, and the knowledge technology strategy. You’ll use the Python language and customary Python libraries as you event firsthand the demanding situations of facing information at scale. become aware of how Python helps you to achieve insights from info units so monstrous that they should be kept on a number of machines, or from info relocating so fast that no unmarried computer can deal with it. This booklet offers hands-on event with the most well-liked Python information technology libraries, Scikit-learn and StatsModels. After interpreting this e-book, you’ll have the forged origin you want to begin a occupation in info technology.

What’s Inside

  • Handling huge data
  • Introduction to computing device learning
  • Using Python to paintings with data
  • Writing information technological know-how algorithms

About the Reader

This publication assumes you are cozy analyzing code in Python or an analogous language, equivalent to C, Ruby, or JavaScript. No past event with facts technology is required.

About the Authors

Davy Cielen, Arno D. B. Meysman, and Mohamed Ali are the founders and handling companions of Optimately and Maiton, the place they specialize in constructing info technology tasks and suggestions in a number of sectors.

Table of Contents

  1. Data technological know-how in a tremendous facts world
  2. The info technology process
  3. Machine learning
  4. Handling huge facts on a unmarried computer
  5. First steps in enormous data
  6. Join the NoSQL movement
  7. The upward push of graph databases
  8. Text mining and textual content analytics
  9. Data visualization to the top user

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Additional resources for Introducing Data Science: Big Data, Machine Learning and More, Using Python tools

Sample text

The landscape doesn’t end with Python libraries, of course. Spark is a new Apachelicensed machine-learning engine, specializing in real-learn-time machine learning. org/. 5 NoSQL databases If you need to store huge amounts of data, you require software that’s specialized in managing and querying this data. Traditionally this has been the playing field of relational databases such as Oracle SQL, MySQL, Sybase IQ, and others. While they’re still the go-to technology for many use cases, new types of databases have emerged under the grouping of NoSQL databases.

By solving several of the problems of traditional databases, NoSQL databases allow for a virtually endless growth of data. These shortcomings relate to every property of big data: their storage or processing power can’t scale beyond a single node and they have no way to handle streaming, graph, or unstructured forms of data. Many different types of databases have arisen, but they can be categorized into the following types: ■ ■ ■ ■ ■ ■ Column databases—Data is stored in columns, which allows algorithms to perform much faster queries.

When you combine data, you have the option to create a new physical table or a virtual table by creating a view. The advantage of a view is that it doesn’t consume more disk space. Let’s elaborate a bit on these methods. JOINING TABLES Joining tables allows you to combine the information of one observation found in one table with the information that you find in another table. The focus is on enriching a single observation. Let’s say that the first table contains information about the purchases of a customer and the other table contains information about the region where your customer lives.

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Introducing Data Science: Big Data, Machine Learning and More, Using Python tools by Davy Cielen, Arno Meysman, Mohamed Ali


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