22. Good Book recommendations for data analysis and mining-sharing of dry goods

1. The data analysis (Douban) book is quite simple. The basic content is involved, and it is clear. Finally, we talked about R as a plus.

Difficulty level: very easy.

2. Beer and diapers (Douban) are the most typical cases.

Difficulty level: very easy.

3. The beauty of data (Douban) An introductory book, each chapter solves a specific problem, and even has code, which is very helpful for understanding the application fields and practices of data analysis.

Difficulty: Easy.

4. Collective intelligent programming (Douban) is the first book to learn data analysis, data mining, and machine learning. The author introduces algorithms in machine learning and data mining through practical examples, which are easy to understand and can execute Python code.

Difficulty level: medium.

5. Machine Learning in Action (Douban) Explain complicated and difficult machine learning algorithms clearly. There are sporadic mathematical formulas, but they are for the purpose of clarity. And Python code. Awesome! At present, the Chinese Emy of Sciences teacher Wang Bin (Weibo: @ Wang Bin _ ictio) has translated this book machine learning practice (Douban ). The quality of this book is very high, and Mr. Wang's translation quality is also very high.

Difficulty level: medium.

6. The recommendation system practice (Douban) is the first book to be read.

Difficulty level: medium.

7. introduction to data mining (Douban) is a good book in Data Mining textbooks in recent years. It has been used as a teaching material by many American universities for data mining and has not been recommended by Mr. Jiawei Han, I personally think that book is not easy for beginners to understand.

Difficulty level: medium.

8. The elements of Statistical Learning (Douban) has a corresponding Chinese version: the basics of Statistical Learning (Douban ). The book is equipped with an R package, which is very nice! You can refer to the code learning algorithm.

Difficulty level: hard.

9. I strongly recommend the statistical learning method (Douban.com), which is the best practice of Teacher Li Hang.

Difficulty level: hard.

10. Pattern Recognition and machine learning (Douban) Classic.

11. Professor Kevin murrphy, a new book published last year in machine learning, is a young and promising representative in the field of machine learning. This book is a masterpiece of him. After writing it, I went to Google. There was no better combination of industry, university, and research.

12. bayesian reasoning and machine learning (Douban) can be read by name. There are many contents in the Bayesian School, there is a picture that summarizes the relationship between the design algorithms in machine learning. It's great.

13. Machine Learning for hackers (Douban) also explains machine learning algorithms through examples. Using R, you can learn R while learning R.

14. probabilistic graphical models (Douban) is a masterpiece. If anyone finishes reading this book, let me know.

15. convex optimization (Douban) is one of the best teaching materials for convex optimization. Course is also very good, Stephen took the paper step by step to push, Figure 1.1 point painting, great.

16. graphical models, exponential families, and variational inference (Douban) is the title of Jordan's old man and his proud disciple Martin J Wainwright on foundation of machine learning research. It can be downloaded for free, it is hard to understand, but once the reading is done, the relevant content of the graphical model can be flattened.

17. Introduction to semi-Supervised Learning (Douban) Semi-supervised learning must read a required book.

18. Learning to rank for Information Retrieval!

19. learning to rank for information retrieval and Natural Language Processing, it can be seen that the research on LTR is profound and greatly contributed by the Emy.

20. scipy and numpy (Douban) can be classified as data analysis books, because numpy and scipy are really powerful.

21. The author of python for data analysis (Douban) is the author of the pandas package. He has read his speech at the scipy conference. The instance is very strong and uses pandas for data analysis!

22. Bad Data Handbook (Douban) is a very interesting book. The author's perspective is very different.

Reprinted from http://www.douban.com/group/topic/49433829/

22. Good Book recommendations for data analysis and mining-sharing of dry goods