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Data science from scratch: first principles with Python

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Varies, see individual formats and editions
Pub. Date:
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Language:
English
Description

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 .

If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today's messy glut of data holds answers to questions no one's even thought to ask. This book provides you with the know-how to dig those answers out.

Get a crash course in Python Learn the basics of linear algebra, statistics, and probability--and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
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ISBN:
9781491901427
9781491904398
149190142
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Grouping Information

Grouped Work ID 9c03fa02-967e-fe58-8b31-0754a87a269a
Full title data science from scratch first principles with python
Author grus joel
Grouping Category book
Last Update 2018-05-21 22:53:12PM
Last Indexed 2018-05-21 23:53:28PM

Solr Details

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author Grus, Joel,
author_display Grus, Joel
collection_catalog Non-Fiction
detailed_location_catalog Bellevue - Adult Non-Fiction
display_description

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.

If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today's messy glut of data holds answers to questions no one's even thought to ask. This book provides you with the know-how to dig those answers out.

  • Get a crash course in Python
  • Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science
  • Collect, explore, clean, munge, and manipulate data
  • Dive into the fundamentals of machine learning
  • Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering
  • Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
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    itype_catalog , Book
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    record_details ils:CARL0000481027|Book|Books|First edition.|English|O'Reilly,|[2015]|xvi, 311 pages : illustrations ; 24 cm., overdrive:72fae62a-b876-4be1-8202-446c18ba55fa|eBook|eBook||English|O'Reilly Media|2015|
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    subject_facet Data structures (Computer science), Database management, Python (Computer program language)
    title_display Data science from scratch : first principles with Python
    title_full Data Science from Scratch First Principles with Python, Data science from scratch : first principles with Python / Joel Grus
    title_short Data science from scratch :
    title_sub first principles with Python
    topic_facet Computer Technology, Data structures (Computer science), Database management, Nonfiction, Python (Computer program language)