Christopher M. Bishop, Pattern Recognition and Machine Learning

09 Dec 2020

PRML: Please see the textbook Christopher M. Bishop, Pattern Recognition and Machine and the slides below. Please note the slides are copied from Reading Group: Pattern Recognition and Machine Learning.

• Slide 01: Chapter 1: Introduction;
• Slide 02: Chapter 2: Probability Distributions
• Slide 03: Chapter 3: Linear Models For Regression;
• Slide 04: Chapter 4: Linear Models For Classification (Slide N/A);
• Slide 05: Chapter 5: Neural Networks;
• Slide 06: Chapter 6: Kernel Methods;
• Slide 07: Chapter 7: Sparse Kernel Machines;
• Slide 08: Chapter 8: Graphical Models;
• Slide 09: Chapter 9: Mixture Models And EM;
• Slide 10: Chapter 10: Approximate Inference;
• Slide 11: Chapter 11: Sampling Methods;
• Slide 12: Chapter 12: Continuous Latent Variables;
• Slide 13: Chapter 13: Sequential Data (1/2);
• Slide 14: Chapter 13: Sequential Data (2/2);
• Slide 15: Chapter 14: Combining Models (Slide N/A);