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Data Science from Scratch: First Principles with Python 2nd Edition
Data Science from Scratch: First Principles with Python 2nd Edition
Data Science from Scratch: First Principles with Python 2nd Edition
Data Science from Scratch: First Principles with Python 2nd Edition
Data Science from Scratch: First Principles with Python 2nd Edition
Data Science from Scratch: First Principles with Python 2nd Edition
Data Science from Scratch: First Principles with Python 2nd Edition

Data Science from Scratch: First Principles with Python 2nd Edition

Tình trạng: Còn hàng
Tác giả: O'Reilly
Loại: Data

Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch.

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Số lượng:

I. THÔNG TIN SẢN PHẨM
Mã sản phẩm : STT564
Nhà xuất bản:  O'Reilly Media; 2nd edition (May 16, 2019)
Tác giả : Joel Grus
Ngôn Ngữ : Tiếng Anh
ISBN      : 1492041130
Số trang ‏ : ‎ 406 pages
Hình thức : Bìa Mềm, IN ĐEN TRẮNG
Loại : Sách gia công
Giấy in : Giấy ngoại định lượng 70msg, viết vẽ và hightlight thoải mái.
Chất lượng : Bản in rõ nét, giá rất tốt cho mọi người.

II. MÔ TẢ SẢN PHẨM

1.Mô tả sản phẩm
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.

2.Tác giả
Joel Grus is a research engineer at the Allen Institute for Artificial Intelligence. Previously he worked as a software engineer at Google and a data scientist at several startups. He lives in Seattle, where he regularly attends data science happy hours.
 

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