https://www.shaorongwang.com/courses/machine-learning/2025/Machine Learning — 2025 MaterialsHugoBlox Kit (https://hugoblox.com)en-UShttps://www.shaorongwang.com/media/sharing.pnghttps://www.shaorongwang.com/courses/machine-learning/2025/https://www.shaorongwang.com/courses/machine-learning/2025/schedule/Mon, 01 Jan 0001 00:00:00 +0000https://www.shaorongwang.com/courses/machine-learning/2025/schedule/<table> <thead> <tr> <th>File</th> <th>Download</th> </tr> </thead> <tbody> <tr> <td>01 Machine Learning and Statistical Learning.pdf</td> <td> </td> </tr> <tr> <td>02 Perceptron.pdf</td> <td> </td> </tr> <tr> <td>03 k-Nearest Neighbors.pdf</td> <td> </td> </tr> <tr> <td>04 Bayesian Classifiers.pdf</td> <td> </td> </tr> <tr> <td>06 Logistic Regression and Maximum Entropy.pdf</td> <td> </td> </tr> <tr> <td>07 Support Vector Machines.pdf</td> <td> </td> </tr> <tr> <td>09 Expectation-Maximization and Extensions.pdf</td> <td> </td> </tr> <tr> <td>13 Introduction to Unsupervised Learning.pdf</td> <td> </td> </tr> <tr> <td>14 Clustering Methods.pdf</td> <td> </td> </tr> <tr> <td>15 Singular Value Decomposition.pdf</td> <td> </td> </tr> <tr> <td>16 Principal Component Analysis.pdf</td> <td> </td> </tr> <tr> <td>Appendix-Distribution-Measures.pdf</td> <td> </td> </tr> <tr> <td>DL/01 Overview Linear Algebra and NDArray.pdf</td> <td> </td> </tr> <tr> <td>DL/03 Derivatives Backpropagation and Complexity.pdf</td> <td> </td> </tr> <tr> <td>DL/04 Linear Methods Basic Optimization and Linear Regression.pdf</td> <td> </td> </tr> <tr> <td>DL/05 Maximum Likelihood Estimation and Logistic Regression.pdf</td> <td> </td> </tr> <tr> <td>DL/06 Multilayer Perceptrons.pdf</td> <td> </td> </tr> <tr> <td>DL/08 Numerical Stability Activation Functions and Hardware.pdf</td> <td> </td> </tr> <tr> <td>DL/11 Convolution and Pooling Layers.pdf</td> <td> </td> </tr> <tr> <td>DL/12 LeNet AlexNet VGG and NiN.pdf</td> <td> </td> </tr> <tr> <td>DL/13 Inception Batch Normalization and Residual Networks.pdf</td> <td> </td> </tr> <tr> <td>DL/15 Image Augmentation Fine-Tuning and Style Transfer.pdf</td> <td> </td> </tr> <tr> <td>DL/16 Object Detection and Computer Vision Training Techniques.pdf</td> <td> </td> </tr> <tr> <td>DL/18 Sequence Models.pdf</td> <td> </td> </tr> <tr> <td>DL/19 Recurrent Neural Networks.pdf</td> <td> </td> </tr> <tr> <td>DL/20 Advanced Recurrent Neural Networks.pdf</td> <td> </td> </tr> <tr> <td>DL/24 Attention Mechanisms.pdf</td> <td> </td> </tr> <tr> <td>DL/24 ViT.pdf</td> <td> </td> </tr> <tr> <td>DL/25 Optimization Problems.pdf</td> <td> </td> </tr> <tr> <td>DL/DM/00 Prerequisites.pdf</td> <td> </td> </tr> <tr> <td>DL/DM/01 AE.pdf</td> <td> </td> </tr> <tr> <td>DL/DM/02 EM.pdf</td> <td> </td> </tr> <tr> <td>DL/DM/03 VAE.pdf</td> <td> </td> </tr> <tr> <td>DL/DM/04 GAN.pdf</td> <td> </td> </tr> <tr> <td>DL/DM/05 Diffusion Model.pdf</td> <td> </td> </tr> <tr> <td>DL/LM/00 Language Model Overview.pdf</td> <td> </td> </tr> <tr> <td>DL/LM/01 Text Preprocessing.pdf</td> <td> </td> </tr> <tr> <td>DL/LM/02 Statistical Language Models.pdf</td> <td> </td> </tr> <tr> <td>DL/LM/03 Word Embeddings.pdf</td> <td> </td> </tr> <tr> <td>DL/LM/04 Sequence-to-Sequence Models.pdf</td> <td> </td> </tr> <tr> <td>DL/LM/05 Pretrained Models.pdf</td> <td> </td> </tr> <tr> <td>Linear-Algebra-Fundamentals-ML.pdf</td> <td> </td> </tr> </tbody> </table>