Viser: Data Science from Scratch - First Principles with Python

Data Science from Scratch
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Data Science from Scratch Vital Source e-bog

Joel Grus
(2019)
O'Reilly Media, Inc
559,00 kr. 503,10 kr.
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Data Science from Scratch - First Principles with Python, 2. udgave

Data Science from Scratch

First Principles with Python
Joel Grus
(2019)
Sprog: Engelsk
O'Reilly Media, Incorporated
499,00 kr. 449,10 kr.
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Detaljer om varen

  • Vital Source searchable e-book (Reflowable pages)
  • Udgiver: O'Reilly Media, Inc (April 2019)
  • ISBN: 9781492041085
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. With this updated second edition, 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.
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Detaljer om varen

  • 2. Udgave
  • Paperback: 500 sider
  • Udgiver: O'Reilly Media, Incorporated (Maj 2019)
  • ISBN: 9781492041139

To really learn data science, you should not only master the tools--data science libraries, frameworks, modules, and toolkits--but also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these 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 the hacking skills you need to get started as a data scientist. Packed with new material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today's messy glut of data.

  • Get a crash course in Python
  • Learn the basics of linear algebra, statistics, and probability--and 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, Naïve 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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