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Metropolis Sampling

arXiv.org Machine Learning

Monte Carlo (MC) sampling methods are widely applied in Bayesian inference, system simulation and optimization problems. The Markov Chain Monte Carlo (MCMC) algorithms are a well-known class of MC methods which generate a Markov chain with the desired invariant distribution. In this document, we focus on the Metropolis-Hastings (MH) sampler, which can be considered as the atom of the MCMC techniques, introducing the basic notions and different properties. We describe in details all the elements involved in the MH algorithm and the most relevant variants. Several improvements and recent extensions proposed in the literature are also briefly discussed, providing a quick but exhaustive overview of the current Metropolis-based sampling's world.


Amazon.com: Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner (9781118729274): Galit Shmueli, Peter C. Bruce, Nitin R. Patel: Books

@machinelearnbot

"…full of vivid and thought-provoking anecdotes... needs to be read by anyone with a serious interest in research and marketing." "Shmueli et al. have done a wonderful job in presenting the field of data mining - a welcome addition to the literature." "Excellent choice for business analysts...The book is a perfect fit for its intended audience." "…extremely well organized, clearly written and introduces all of the basic ideas quite well." Data Mining for Business Analytics: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner, Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies.


Wiley's list of leading and interesting blogs to follow

@machinelearnbot

Here are the top 10, in alphabetical order. Wiley's full list mentions many interesting statistical blogs.


Sports Reference Sports Stats, fast, easy, and up-to-date Sports-Reference.com

#artificialintelligence

Our aim is to be the easiest-to-use, fastest, most complete sources for sports statistics anywhere. Complete postseason and managerial data is included as well. Find statistics for your favorite player, team, or league. The site also includes sections for coaches, awards, leaders, and the playoffs. A user favorite is the Play Index custom leaderboards.


4 easy steps to becoming a data scientist

@machinelearnbot

Buy a book on modern data science, avoid statistics textbooks re-labeled as data science like plague: they will lead you to nowhere. Any public-domain stuff that's been invented 50 years ago will lead to a job that will eventually be replaced by a robot - we are working on this to make it happen. If you have an analytic background, my book is a good start. Older versions are still available for free, but the Wiley version is much more organized and easy to read, and costs less than $25. Other books can be found in the reference section below.