Doing Data Science

But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.

Doing Data Science

Author: Cathy O'Neil

Publisher: "O'Reilly Media, Inc."

ISBN: 144936389X

Page: 408

View: 418

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

Related Books:

Doing Data Science
Language: en
Pages: 408
Authors: Cathy O'Neil, Rachel Schutt
Categories: Computers
Type: BOOK - Published: 2013-10-09 - Publisher: "O'Reilly Media, Inc."

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s
Doing Data Science
Language: en
Pages:
Authors: Cathy O'Neil, Rachel Schutt
Categories: Computers
Type: BOOK - Published: 2013 - Publisher:

Books about Doing Data Science
Doing Data Science in R
Language: en
Pages: 456
Authors: Mark Andrews
Categories: Psychology
Type: BOOK - Published: 2021-03-27 - Publisher: SAGE

This approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis. Introducing the fundamentals of data science and R before moving into more advanced topics like Multilevel Models and Probabilistic Modelling with Stan, it builds knowledge and
Doing Data Science in R
Language: en
Pages: 456
Authors: Mark Andrews
Categories: Social Science
Type: BOOK - Published: 2021-03-31 - Publisher: SAGE

This approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis. Introducing the fundamentals of data science and R before moving into more advanced topics like Multilevel Models and Probabilistic Modelling with Stan, it builds knowledge and
R for Data Science
Language: en
Pages: 520
Authors: Hadley Wickham, Garrett Grolemund
Categories: Computers
Type: BOOK - Published: 2016-12-12 - Publisher: "O'Reilly Media, Inc."

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R