Practical Statistics for Data Scientists 50+ Essential Concepts Using R and Python 2nd Edition

I. THÔNG TIN SẢN PHẨM
Mã sản phẩm : STT308
Nhà xuất bản:  O'Reilly Media; 2nd edition (June 2, 2020)
Tác giả : Peter Bruce, Andrew Bruce, Peter Gedeck
Ngôn Ngữ : Tiếng Anh
ISBN      : 149207294X
Số trang    :368 pages
Hình thức : Bìa Mềm, IN ĐEN TRẮNG
Loại : Sách gia công đóng gáy keo chắc chắn chất lượng cao
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
Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not.

Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.

With this book, you’ll learn:

    Why exploratory data analysis is a key preliminary step in data science
    How random sampling can reduce bias and yield a higher-quality dataset, even with big data
    How the principles of experimental design yield definitive answers to questions
    How to use regression to estimate outcomes and detect anomalies
    Key classification techniques for predicting which categories a record belongs to
    Statistical machine learning methods that "learn" from data
    Unsupervised learning methods for extracting meaning from unlabeled data.

2. Tác giả
Peter Bruce is the Founder and Chief Academic Officer of the Institute for Statistics Education at Statistics.com, which offers about 80 courses in statistics and analytics, roughly half of which are aimed at data scientists. He has authored or co-authored several books in statistics and analytics, and he earned his Bachelor’s degree at Princeton, and Masters degrees at Harvard and the University of Maryland.

Andrew Bruce, Principal Research Scientist at Amazon, has over 30 years of experience in statistics and data science in academia, government and business. The co-author of Applied Wavelet Analysis with S-PLUS, he earned his bachelor’s degree at Princeton, and PhD in statistics at the University of Washington

Peter Gedeck, Senior Data Scientist at Collaborative Drug Discovery, specializes in the development of machine learning algorithms to predict biological and physicochemical properties of drug candidates. Co-author of Data Mining for Business Analytics, he earned PhD’s in Chemistry from the University of Erlangen-Nürnberg in Germany and Mathematics from Fernuniversität Hagen, Germany.