{"product_id":"9783319644097","title":"Probability and Statistics for Computer Science","description":"\u003cp\u003eThis textbook is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning.\u003c\/p\u003e\u003cp\u003eWith careful treatment of topics that fill the curricular needs for the course, \u003ci\u003eProbability and Statistics for Computer Science\u003c\/i\u003e features:\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e•   A treatment of random variables and expectations dealing primarily with the discrete case.\u003cbr\u003e\u003c\/p\u003e•   A practical treatment of simulation, showing how many interesting probabilities and expectations can be extracted, with particular emphasis on Markov chains.\u003cp\u003e\u003c\/p\u003e•   A clear but crisp account of simple point inference strategies (maximum likelihood; Bayesian inference) in simple contexts. This is extended to cover some confidence intervals, samples and populations for random sampling with replacement, and the simplest hypothesis testing.\u003cp\u003e\u003c\/p\u003e\u003cp\u003e•   A chapter dealing with classification, explaining why it’s useful; how to train SVM classifiers with stochastic gradient descent; and how to use implementations of more advanced methods such as random forests and nearest neighbors.\u003c\/p\u003e•   A chapter dealing with regression, explaining how to set up, use and understand linear regression and nearest neighbors regression in practical problems.\u003cp\u003e\u003c\/p\u003e•   A chapter dealing with principal components analysis, developing intuition carefully, and including numerous practical examples. There is a brief description of multivariate scaling via principal coordinate analysis.\u003cp\u003e\u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003e•   A chapter dealing with clustering via agglomerative methods and k-means, showing how to build vector quantized features for complex signals.\u003c\/p\u003e\u003cp\u003eIllustrated throughout, each main chapter includes many worked examples and other pedagogical elements such as \u003c\/p\u003eboxed Procedures, Definitions, Useful Facts, and Remember This (short tips). Problems and Programming Exercises are at the end of each chapter, with a summary of what the reader should know.  \u003cp\u003e\u003c\/p\u003eInstructor resources include a full set of model solutions for all problems, and an Instructor's Manual with accompanying presentation slides.\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003ePublication Year: \u003c\/strong\u003e2018\u003cbr\u003e\u003cstrong\u003eImprint: \u003c\/strong\u003eSpringer International Publishing\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003eFormat: H\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003eWeight (Gram): 1651\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003e\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003e\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003e\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003e\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003e\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003e\u003c\/p\u003e","brand":"David Forsyth","offers":[{"title":"Default Title","offer_id":41255710556338,"sku":"9783319644097","price":1438303.74,"currency_code":"IDR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0502\/5382\/4178\/products\/3319644092.01_SCLZZZZZZZ.jpg?v=1635861690","url":"https:\/\/readabook.store\/en-id\/products\/9783319644097","provider":"READABOOK BY ALKEM","version":"1.0","type":"link"}