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所在平台: Udemy |
课程主页: https://www.udemy.com/course/probability-and-statistics-for-machine-learning-1/
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**课程名称：** 应用概率导论 (Introduction To Applied Probability) **课程概述：** 本课程旨在以简明易懂的方式，帮助学习者掌握机器学习、数据科学、计算机科学和电气工程等领域所需的概率论基础知识。课程内容源于概率论理论，并深入浅出地讲解了统计学这一衍生的科学分支。 **课程亮点：** * **超过35个视频讲解：** 全面覆盖概率论的基础概念。 * **超过35个示例与详细解答：** 帮助学习者巩固理解，检验学习效果。 * **结构清晰：** 课程内容组织合理，学习路径明确。 **课程主要章节：** * 引言 (Introduction) * 一些基本定义 (Some Basic Definitions) * 概率的数学定义 (Mathematical Definition of Probability) * 一些重要符号 (Some Important Symbols) * 重要结果 (Important Results) * 条件概率 (Conditional Probability) * 全概率定理 (Theorem of Total Probability) * 贝叶斯定理 (Baye's Theorem) * 伯努利试验 (Bernoulli's Trials) * 不可数均匀空间 (Uncountable Uniform Spaces)
HOW INTRODUCTION TO APPLIED PROBABILITY IS SET UP TO MAKE COMPLICATED PROBABILITY AND STATISTICS EASYThis course deals with concepts required for the study of Machine Learning and Data Science. Statistics is a branch of science that is an outgrowth of the Theory of Probability. Probability & Statistics are used in Machine Learning, Data Science, Computer Science and Electrical Engineering.This 35+ lecture course includes video explanations of everything from Fundamental of Probability, and it includes more than 35+ examples (with detailed solutions) to help you test your understanding along the way. Introduction To Applied Probability is organized into the following sections:IntroductionSome Basic DefinitionsMathematical Definition of ProbabilitySome Important SymbolsImportant ResultsConditional ProbabilityTheorem of Total ProbabilityBaye's TheoremBernoulli's TrialsUncountable Uniform Spaces
