Bishop - Pattern Recognition And Machine Learning - Springer 2006

Amazon 排名前5资源 Preface Mathematical Notation 1.Introduction 2.Probability Distribution 3.Linear Models for Regression 4. Linear Models for Classification 5. Neural Networks 6. Kernel Methods 7. Sparse Kernel Machines 8.Graphical Models 9.Mixture Models and EM 10. Approximate Inference 11.Sampling Methods 12.Continuous Latent Variables 13. Sequential Data 14.Combining Models