Probability and Statistics for Machine Learning: A Textbook
English | 2024 | ISBN: 3031532813 | 538 Pages | PDF (True) | 43 MB
From probability to machine learning: Many machine learning applications are addressed using probabilistic models, whose parameters are then learned in a data-driven manner. Chapters 6 through 9 explore how different models from probability and statistics are applied to machine learning. Perhaps the most important tool that bridges the gap from data to probability is maximum-likelihood estimation, which is a foundational concept from the perspective of machine learning. This concept is explored repeatedly in these chapters.
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