Collective Intelligence Programming - Python Algorithm Application This book takes machine learning and computational statistics as the theme background, and specifically describes how to mine and analyze data and resources on the Web, how to analyze user experience, marketing, personal taste and many other information, and draw useful conclusions, and use complex algorithms to obtain, collect and analyze user data and feedback information from Web sites in order to create new user value and business value. The book is detailed, including collaborative filtering technology (to achieve the function of recommending related products), cluster data analysis (to discover similar data subsets in large-scale data sets), search engine core technology (crawlers, indexes, query engines, PageRank algorithms, etc.), optimization algorithms for searching massive information and analyzing and drawing conclusions, Bayesian filtering technology (spam filtering, text filtering), using decision tree technology to achieve prediction and decision modeling functions, information matching technology of social networks, machine learning and artificial intelligence applications, etc. This book is an excellent choice for Web developers, architects, application engineers, etc.
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