Week 6: Machine Learning BasicsIntroduction to Machine Learning, types of ML, and real-world examples.
Definition of machine learning and its types (supervised, unsupervised, reinforcement)
Basic algorithms in machine learning (linear regression, logistic regression, decision trees, k-means clustering, etc.)
Understanding the concept of training and testing data
Basics of model evaluation (accuracy, precision, recall, ROC curve, etc.)
Demonstration of a simple machine learning model using Python or another tool