توضیحات

آماده سازی ارسال کتاب های زبان اصلی بین 8 تا 12 روز کاری زمانبر می باشد.
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https://www.amazon.com/Data-Mining-Machine-Learning-Fundamental/dp/1108473989/ref=sr_1_1?crid=CCPLLXT8RHT2&dib=eyJ2IjoiMSJ9.aVscyt9mLNee43z3_oiLww3zu9usApSA6nloVKO35rVW20PjNTAxhL4jxcf8dJDABLafpLqxPfdxKnQElrIX472ZrJo4a6dAVDWavFqI8GLA-_XHFrlSuGOe9yx4NwrGkrTzrsCjmFO4iksaoHXJcpv6OsvVp-iU0yhAvKZZekiWnzcYiJ74JIOORZwbxfMwJZrutBiZC_uDujMzjYw6jZAEykJnPNj5QldridEoG_8.WcyoM_ZLQNiHWY3gKL7z-5NZbqoNhcr7Djfbl-VyzB8&dib_tag=se&keywords=Data+Mining+and+Machine+Learning&qid=1726847178&sprefix=data+mining+and+machine+learning%2Caps%2C599&sr=8-1
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Review
‘This book by Mohammed Zaki and Wagner Meira, Jr is a great option for teaching a course in data mining or data science. It covers both fundamental and advanced data mining topics, explains the mathematical foundations and the algorithms of data science, includes exercises for each chapter, and provides data, slides and other supplementary material on the companion website.' Gregory Piatetsky-Shapiro, Founder of the Association for Computing Machinery's Special Interest Group on Knowledge Discovery and Data Mining (ACM SIGKDD)

‘World-class experts, providing an encyclopedic coverage of all datamining topics, from basic statistics to fundamental methods (clustering, classification, frequent itemsets), to advanced methods (SVD, SVM, kernels, spectral graph theory, deep learning). For each concept, the book thoughtfully balances the intuition, the arithmetic examples, as well the rigorous math details. It can serve both as a textbook, as well as a reference book.' Christos Faloutsos, Carnegie Mellon University, Pennsylvania, and winner of the ACM SIGKDD Innovation Award