Book
Bayesian Reasoning and Machine Learning
| Identifier | --davidbarbe-446 |
|---|---|
| Penulis / Pengarang | David Barber |
| Kata Kunci | Machine Learning |
| Tanggal Publikasi | 16 Sep 2020 |
| Bahasa | Bahasa Inggris |
| Abstrak / Deskripsi | We live in a world that is rich in data, ever-increasing in scale. This data comes from many di event sources in science (bioinformatics, astronomy, physics, environmental monitoring) and commerce (customer databases, financial transactions, engine monitoring, speech recognition, surveillance, search). Possessing the knowledge as to how to process and extract value from such data is, therefore, a key and increasingly important skill. Our society also expects ultimately to be able to engage with computers in a natural manner so that computers can `talk' to humans, `understand' what they say, and `comprehend' the visual world around them. These are dicult large-scale information processing tasks and represent grand challenges for computer science and related elds. Similarly, there is a desire to control increasingly complex systems, possibly containing many interacting parts, such as in robotics and autonomous navigation. Successfully mastering such systems requires an understanding of the processes underlying their behavior. Processing and making sense of such large amounts of data from complex systems is, therefore, a pressing modern-day concern and will likely remain so for the foreseeable future. |
| Hak Cipta | Copyright (c) 2001 by . Verbatim copying and distribution of this entire article is permitted by author in any medium, provided this notice is preserved. |
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