Machine Learning for Data Streams - with Practical Examples in MOA (The MIT Press)

[ FreeCourseWeb.com ] Machine Learning for Data Streams: with Practical Examples in MOA (The MIT Press)



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English | 2018 | ISBN-13: 978-0262037792 | 288 Pages | True PDF | 21.36 MB



A 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.



Today 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 nstrates 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.



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