Understanding Supervised Machine Learning

Introduction to Machine Learning
Machine learning process - AI vs ML vs DL - Types: supervised, unsupervised, reinforcement learning - Types of supervised learning - Curse of dimensionality - Overfitting versus underfitting - Bias Variance tradeoff
- General principles in machine learning - Feature extraction - Training, testing and validation set - k-fold cross validation - confusion matrix - Performance metrics - ROC curve
Practice: Demonstrate k-fold cross validation and evaluation of performance metrics.