{"product_id":"machine-learning-for-data-streams-with-practical-examples-in-moa-paperback","title":"Machine Learning for Data Streams: With Practical Examples in Moa - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eAlbert Bifet\u003c\/b\u003e (Author), \u003cb\u003eRicard Gavalda\u003c\/b\u003e (Author), \u003cb\u003eGeoffrey Holmes\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003cb\u003eA hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework.\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003eToday many information sources--including sensor networks, financial markets, social networks, and healthcare monitoring--are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. \u003cp\u003e\u003c\/p\u003eThe book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003eAlbert Bifet is Professor of Computer Science at Télécom ParisTech.\u003cbr\u003eRicard Gavaldà is Professor of Computer Science at the Politècnica de Catalunya, Barcelona.\u003cbr\u003eGeoff Holmes is Professor and Dean of Computing at the University of Waikato in Hamilton, New Zealand.\u003cbr\u003eBernhard Pfahringer is Professor of Computer Science at the University of Auckland, New Zealand.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 288\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.78 x 9 x 7 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e May 09, 2023\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":71360937885949,"sku":"9780262547833","price":106.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/3414\/0157\/files\/SQjhX9DG2Z9780262547833.webp?v=1790185852","url":"https:\/\/booktolia.com\/products\/machine-learning-for-data-streams-with-practical-examples-in-moa-paperback","provider":"booktolia","version":"1.0","type":"link"}