artificial intelligence and machine learning books

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

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

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

~ ~): 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

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

approximation and generalized beliefPropagation algorithms.pdfLoopy belief propagation for approximate inference an empirical study.pdfLoopy belief propagationdeletion AP (affinity propagation ): L-BFGS:On the limited memory BFGS method for large scale optimizationscalingIIS:Iis.pdf ========================================================== ======================================Theoretical part:Probability graph (Probabilistic networks ):An Introduction to Variational Methods for graphical mode