Machine Learning 06: PAC Theory
Course Notes of Professor Tom Mitchell Machine Learning Course @ CMU, 2017
Computational Learning Theory
What general laws constrain......
380
Hubert Wang
Machine Learning 05: Graphical Models
Course Notes of Professor Tom Mitchell Machine Learning Course @ CMU, 2017
Graphical Models
Key Ideas:
Conditional Independence as......
589
Machine Learning 04: DNN, CNN, RNN, and Representation Learning
Course Notes of Professor Tom Mitchell Machine Learning Course @ CMU, 2017
Why not Logistic Regression?
We like logistic regression,......
2366
Machine Learning 03: Gaussian Naïve Bayes and Logistic Regression
Course Notes of Professor Tom Mitchell Machine Learning @ CMU
Naïve Bayes with Continuous X
In order to train a Naive Bayes classifi......
901
Machine Learning 02: MLE, MAP, and Naïve Bayes
Course Notes of Professor Tom Mitchell Machine Learning @ CMU
Probablistic learning
Probablistic function approximation:
instead......
476
Machine Learning 01: Decision Tree, Entropy, and Overfitting
Course Notes of Professor Tom Mitchell Machine Learning @ CMU
Machine Learning is the study of algorithms that:
Improve their p......
1468