Programming for AI (AI504, Fall 2023), Class 2: Basic Machine Learning

Basic machine learning:
- Supervised, unsupervised, reinforcement learning
- Optimization: Objective function, loss function, local/global minimum
- Gradient descent, stochastic gradient descent
- Model evaluation: Evaluation metric, train/validation/test split, N-fold cross validation
- Overfitting & underfitting
- Curse of dimensionality
- Regularization
- Popular classifiers: Logistic regression, SVM, decision tree
- Ensembles: Bagging, boosting
- Popular clustering: K-means clustering, mixture of gaussians

[Ganesha_Yadav]

please for the love of god do not stop uploading these videos under any circumstances