A Hands-On Introduction to Data Science

ISBN-13: 9781108472449 / Angielski / Twarda / 2020 / 424 str.

Chirag (University of Washington) Shah

Opis

A practical introduction to data science with a low barrier entry, this textbook is well-suited to students from a range of disciplines. Assuming no prior knowledge of the subject, the hands-on exercises and real-life application of popular data science tools are accessible even to students without a strong technical background.

Recenzje

'Chirag's extensive experience as a teacher shines through in this textbook, which lives up to its promise to be a 'hands on' introduction to data science. Students have a chance to apply their learning to real-life examples from diverse fields, with hands-on examples that build on basic techniques and utilize tools of data science practice throughout the book. I am particularly pleased to see him weave human issues into his approach, putting principles ahead of particular tools and pointing to ethical challenges at various stages of working with data to help his audience develop an appreciation of ways context and interpretation shape data practices. He exposes students to a more nuanced perspective in which human as well as machine input shapes data science outcomes. It is an awareness that we all will need if we are to use data appropriately to tackle the complex challenges we face today.' Theresa Dirndorfer Anderson

Spis treści

Part I. Introduction: 1. Introduction; 2. Data; 3. Techniques; Part II. Tools: 4. UNIX; 5. Python; 6. R; 7. MySQL; Part III. Machine Learning: 8. Machine learning introduction and regression; 9. Supervised learning; 10. Unsupervised learning; Part IV. Applications and Evaluations: 11. Hands-on with solving data problems; 12. Data collection, experimentation and evaluation.

O autorze

Shah, Chirag Chirag Shah is an Associate Professor of Information and Computer Science at Rutgers University, New Jersey. He investigates issues of search and recommendations using data mining and machine learning. Dr Shah received his M.S. in Computer Science from the University of Massachusetts, Amherst, and his Ph.D. in Information Science from the University of North Carolina, Chapel Hill. He directs the InfoSeeking Lab, supported by awards from the National Science Foundation, the National Institute of Health, the Institute of Museum and Library Services, as well as Amazon, Google, and Yahoo. He was a Visiting Research Scientist at Spotify and has served as a consultant to the United Nations Data Analytics on various data science projects. He is currently working on large-scale e-commerce data and machine learning problems as Amazon Scholar.