Practical Data Science with R ペーパーバック – 2014/4/22
Nina Zumel co-founded Win-Vector, a data science consulting firm in San Francisco. She holds a PH.D. in robotics from Carnegie Mellon and was a content developer for EMC's Data Science and Big Data Analytics Training Course. Nina also contributes to the Win-Vector Blog, which covers topics in statistics, probability, computer science, mathematics and optimization.
John Mount co-founded Win-Vector, a data science consulting firm in San Francisco. He has a Ph.D. in computer science from Carnegie Mellon and over 15 years of applied experience in biotech research, online advertising, price optimization and finance. He contributes to the Win-Vector Blog, which covers topics in statistics, probability, computer science, mathematics and optimization.
- 出版社 : Manning Publications; 第1版 (2014/4/22)
- 発売日 : 2014/4/22
- 言語 : 英語
- ペーパーバック : 416ページ
- ISBN-10 : 1617291560
- ISBN-13 : 978-1617291562
- 寸法 : 18.75 x 2.29 x 23.5 cm
- Amazon 売れ筋ランキング: - 421,936位洋書 (の売れ筋ランキングを見る洋書)
The book organization is well thought out as well. The chapter content is of high quality with right amount of theory and R code to apply them in practice. Data science, being a broadly scoped advanced skill, can only be learnt by doing it. Personally, being an aspiring Data Scientist, I already studied a good amount of literature on Data Mining and Big Data. However, I am not involved in any real life project. So my initial expectation was to gain the experience through case studies. However, as every project is different, you will need to juggle between different tools and evaluate the effectiveness. So the book's approach of presenting only the most common modeling techniques and not using case studies is largely justified. Practical takeaways at the end of the chapter is also very useful.
Overall the book fulfills it's promises set out at the beginning of the book. However, "Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining" by Glenn J. Myatt might be a good supplementary title for a beginner in Data Science. Also to get advanced R skills, you will need to pick from other popular R titles.
Disclaimer: I received a e-copy of the book from Manning for review.