1 Preparatory knowledge 2 Perceptron concept 3 Learning strategies of perceptron 4 Perceptron learning algorithm 5 Convergence of perceptron learning algorithm 6 Dual form of perceptron learning algorithm

1 A Case 2 Least Squares Method 3 From Linear to Nonlinear: Using Linear Model 4 How Regression Got Its Name 5 Probability Interpretation 6 Bias–Variance Dilemma

1 Linear Algebra Notations and Fundamental Concepts Matrix Multiplication Operational Properties Linear Space Quadratic Form and Positive Definite Matrix Matrix Calculus 2 Probability Theory Probability Space Random Variable and Its Distribution Numerical Characteristics of Random Variables Conditional Expectation Jenson’s Inequality

1 Definition of Statistical Learning 2 Application Case of Statistical Pattern Recognition 3 SPR System Framework and Design Cycle 4 Basic Concepts 5 Machine Learning in Different AI Disciplines

一、专业发展概述 三、教学工作 四、科学研究 五、教学条件 二、学术队伍 六、存在的问题

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