best machine learning books 2017

Recommended BooksHere is a list of books which I had read and feel it was worth recommending to friends who was interested in computer Scie nCE.Machine Learningpattern recognition and machine learningChristopher M. BishopA new treatment of classic machine learning topics, such as classification, regression, and time se

is very complete, combined with the later exercise with the R language of their own contact, for understanding the basic methods of machine learning is very helpful, such as: Logistic,ridge regression. The book can also be downloaded directly to the electronic version on the author's website. http://statweb.stanford.edu/~tibs/ElemStatLearn/ With a theoretical basis, combined with a number of professors of

~ ~): Machine learning, data mining (the second half of the main entry): "Introduction to Data Mining" read a few chapters, feel good. Read the review again. "Machine learning" Stanford Open Class is the main. "Linear Algebra", seventh edition, American Steven J.leon There are examples of applications, looking at

and is easily downloaded and modified by the reader.The following books will not be introduced, share the graphic coverHere is still to recommend my own built Python development Learning Group: 725479218, the group is the development of Python, if you are learning Python, small series welcome you to join, everyone is the software Development Party, not regularly

Starter Book List The beauty of mathematics PDFThe author Wu Everyone is familiar with it. The application of mathematics in the fields of machine learning and natural language processing is described in a very popular language. "Programming Collective Intelligence" ("collective Wisdom Programming") PDFAuthor Toby Segaran is also the author of Beautifuldata:the Stories Behind Elegant Data Solutions (t

prediction Naturual Language Processing Coursera Course Book on NLP NLTK NLP W/python Foundations of statistical Language processing Probability Statistics Thinking Stats-book + Python Code From algorithms to Z-scores-book The Art of R Programming-book (not finished) All of Statistics Introduction to statistical thought Basic probability theory Introduction to probability Principle of uncertainty Probability Statistics Cookbo

Starter Book List The beauty of mathematics PDFThe author Wu Everyone is familiar with it. The application of mathematics in the fields of machine learning and natural language processing is described in a very popular language. "Programming Collective Intelligence" ("collective Wisdom Programming") PDFAuthor Toby Segaran is also the author of Beautifuldata:the Stories Behind Elegant Data Solutions (t

Links: Http://suanfazu.com/t/topic/15 Starter Book list The beauty of mathematics PDF586The author Wu Everyone is familiar with it. The application of mathematics in the fields of machine learning and natural language processing is described in a very popular language. "Programming Collective Intelligence" ("collective Intelligence Programming") PDF343Author Toby Segaran is also the author of Beautifu

Here is a list of books which I had read and feel it was worth recommending to friends who was interested in computer Scie nCE.Machine Learningpattern recognition and machine learningChristopher M. BishopA new treatment of classic machine learning topics, such as classification, regression, and time series analysis fro

Recommended BooksHere is a list of books which I had read and feel it was worth recommending to friends who was interested in computer Scie nCE.Machine Learningpattern recognition and machine learningChristopher M. BishopA new treatment of classic machine learning topics, such as classification, regression, and time se

What machine learning programs have been the most watched in 2017 years. Mybridge a list of top 30 for us, with GitHub links attached to all of the following items. We compared nearly 8,800 Kaiyuan machine learning programs and selected the best of the 30. This is a very co

/ EMNLP 2017:Https://ku.cloud.panopto.eu/Panopto/Pages/Sessions/List.aspx Researchers have also begun releasing low-threshold tutorials and summary papers on arXiv. The following are my favorites in the past year. Deep Reinforcement Learning: overviewDeep Reinforcement Learning: An OverviewHttps://arxiv.org/abs/1701.07274

written text can really deepen the understanding of the problem, and constantly self-thinking. After all, I write these things not for the sake of books, but to accumulate the key content of learning flexibly, and to do better knowledge management. Of course, it would be better if it helped the reader.Reprint please indicate the author Jason Ding and its provenanceGitHub home page (http://jasonding1354.git

other purpose is to benefit later learning younger sister, 2017 exam content and 2016 exam content very much like, I think he this person is difficult to change, after all, a ppt for 5-6 years,---- The test questions and I wrote the source code (after the examination of the sources have not changed, but the function has been implemented, the code is not good, you can refer to the line):Link: https://pan.ba

I recently want to learn python deep learning, because I want to use python for Image Recognition and related entry books. The best Chinese. It is to give a picture to identify what the plot looks like. I recently want to learn python deep learning, because I want to use python for Image Recognition and related entry books