Requirements: .ePUB, .PDF reader, 41.5 MB
Overview: This book covers probability and statistics from the Machine Learning perspective. Most of Machine Learning is directly or indirectly related to probability and statistics. After all, Machine Learning is all about making predictions based on data, which inevitably leads to statistical methods. These statistical methods are often couched as models, which use probabilities to quantify the likelihoods of events. Therefore, having a strong background in probability and statistics is critical. The familiarity required with probability and statistics often goes well beyond what is taught in undergraduate curricula. As a result, this presents a challenge to beginners in the field. In many cases, the type of techniques required from probability and statistics are specific to Machine Learning, which is not covered by generic courses on probability and statistics. This book therefore develops a treatment of probability and statistics from the specific perspective of Machine Learning. This book teaches probability and statistics with a specific focus on Machine Learning applications. As a natural consequence of this approach, many key concepts in Machine Learning are covered in detail. Therefore, it is possible to learn a significant amount of Machine Learning while learning probability and statistics from this book. The book contains over 200 worked examples in order to elucidate key concepts.
Genre: Non-Fiction > Tech & Devices
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