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Titlebook: Machine Learning and Artificial Intelligence; Ameet V Joshi Book 20201st edition Springer Nature Switzerland AG 2020 Artificial Intelligen

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樓主: 天真無邪
11#
發(fā)表于 2025-3-23 13:18:01 | 只看該作者
12#
發(fā)表于 2025-3-23 14:05:51 | 只看該作者
Book 20201st editionking at the field from only a theoretical or only a practical perspective, this book unifies both perspectives to give holistic understanding. The first part introduces the concepts of AI and ML and their origin and current state. The second and third parts delve into conceptual and theoretic aspect
13#
發(fā)表于 2025-3-23 20:12:22 | 只看該作者
14#
發(fā)表于 2025-3-24 01:09:14 | 只看該作者
Support Vector Machinesd also how it is extended for solving the problems of regression. Theory of SVM proposed an elegant solution towards optimization and generalization and more importantly was extremely successful in getting results that neural network based methods only hoped for at the time.
15#
發(fā)表于 2025-3-24 04:39:32 | 只看該作者
Probabilistic Modelsant to study these wide variety of distributions one after another, I would highly recommend to go through them nonetheless. These distributions and their specific properties are quite important in understanding the variety of ways in which one can expect the data to be distributed in. This knowledge can be invaluable in data exploration.
16#
發(fā)表于 2025-3-24 09:01:34 | 只看該作者
Time Series Modelsled as static by taking snapshots of the data at specific times. However, this approach can only help to certain extent, and in order to solve the problems in dynamic data ultimately user needs to employ one of the techniques described here or deep neural networks as described in chapter dedicated on that topic.
17#
發(fā)表于 2025-3-24 10:50:52 | 只看該作者
Introduction to AI and ML, he/she can directly skip to corresponding part in the book. If the user is coming to the book in a fresh perspective, I would advise to go sequentially, however, if the user is already familiar with certain aspects of the area and want to expand the knowledge about specific topics, he/she is free to jump to different parts.
18#
發(fā)表于 2025-3-24 17:08:37 | 只看該作者
19#
發(fā)表于 2025-3-24 21:48:00 | 只看該作者
20#
發(fā)表于 2025-3-25 01:29:06 | 只看該作者
Emerging Trends in Machine Learningsuccessful in delivering on the promise is likely to change the way we look at machine learning in general. I am only going to touch up on these areas to give the reader a glimpse into the future of machine learning and artificial intelligence.
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