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.
"synopsis" may belong to another edition of this title.
Joel Grus is a software engineer at Google. Before that he worked as a data scientist at multiple startups. He lives in Seattle, where he regularly attends data science happy hours.
"About this title" may belong to another edition of this title.
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