Download or Read online **Probability for Statistics and Machine Learning** full in PDF, ePub and kindle. this book written by Anirban DasGupta and published by Springer Science & Business Media which was released on 17 May 2011 with total page 784 pages. We cannot guarantee that Probability for Statistics and Machine Learning book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. This book provides a versatile and lucid treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine learning. It is written in an extremely accessible style, with elaborate motivating discussions and numerous worked out examples and exercises. The book has 20 chapters on a wide range of topics, 423 worked out examples, and 808 exercises. It is unique in its unification of probability and statistics, its coverage and its superb exercise sets, detailed bibliography, and in its substantive treatment of many topics of current importance. This book can be used as a text for a year long graduate course in statistics, computer science, or mathematics, for self-study, and as an invaluable research reference on probabiliity and its applications. Particularly worth mentioning are the treatments of distribution theory, asymptotics, simulation and Markov Chain Monte Carlo, Markov chains and martingales, Gaussian processes, VC theory, probability metrics, large deviations, bootstrap, the EM algorithm, confidence intervals, maximum likelihood and Bayes estimates, exponential families, kernels, and Hilbert spaces, and a self contained complete review of univariate probability.

# Probability for Statistics and Machine Learning

**Produk Detail:**

- Author : Anirban DasGupta
- Publisher : Springer Science & Business Media
- Pages : 784 pages
- ISBN : 9781441996343
- Release : 17 May 2011
- Rating : /5 from reviews