Probability and Statistics for Data Science

Product description Review 'Fernandez-Granda's Probability and Statistics for Data Science is a comprehensive yet approachable treatment of the fundamentals required of all aspiring Data Scientists-whether they be in academia, industry or elsewhere. The language is clear and precise, and it is one of the best-organized treatments of this material I have ever seen. With lucid examples and helpful exercises, it deserves to be the leading text for these topics among undergraduate and graduate students in this technical, fast-moving discipline. Instructors take note!' Arthur Spirling, Princeton University'If you're mathematically inclined and want to master the foundations of data science in one go, this book is for you. It covers a broad range of essential modern topics - including nonparametric methods, causal inference, latent variable models, Bayesian approaches, and a thorough introduction to machine learning - all illustrated with an abundance of figures and real-world data examples. Highly recommended.' David Rosenberg, Office of the CTO, Bloomberg Book Description A self-contained introduction to probability and statistics for data science with examples involving real-world datasets. About the Author Carlos Fernandez-Granda is Associate Professor of Mathematics and Data Science at New York University, where he has taught probability and statistics to data science students since 2015. The goal of his research is to design and analyze data science methodology, with a focus on machine learning, artificial intelligence, and their application to medicine, climate science, biology, and other scientific domains. Read more