📄️ Supervised Learning
A deep dive into supervised learning: regression, classification, and the relationship between features and targets.
📄️ Unsupervised Learning
Discovering patterns in unlabeled data through clustering, association, and dimensionality reduction.
📄️ Semi-Supervised Learning
Combining small amounts of labeled data with large amounts of unlabeled data to improve model accuracy and reduce labeling costs.
📄️ Self-Supervised Learning
How AI learns by predicting missing parts of its own input, powering Large Language Models and Computer Vision.
📄️ Reinforcement Learning
Understanding the Agent-Environment loop, reward signals, and how AI learns to make optimal decisions in dynamic systems.