Machine Learning (ML)
Machine Learning (ML)
Machine Learning is a branch of Artificial Intelligence (AI) that enables systems to learn from data and improve performance without being explicitly programmed.
Instead of following fixed rules, ML models identify patterns in data and make predictions or decisions based on experience.
Types of Machine Learning
Supervised Learning – Learns from labeled data
(Regression, Classification)
Unsupervised Learning – Finds hidden patterns in unlabeled data
(Clustering, Dimensionality Reduction)
Reinforcement Learning – Learns through trial and error using rewards
Core ML Concepts
Data collection and preprocessing
Feature engineering
Model training and evaluation
Overfitting vs underfitting
Bias–variance tradeoff
Common Algorithms
Linear & Logistic Regression
Decision Trees & Random Forests
Support Vector Machines (SVM)
K-Means Clustering
Neural Networks
Real-World Applications
Recommendation systems
Fraud detection
Image and speech recognition
Predictive analytics
Autonomous systems
Why Machine Learning Matters
Automates decision-making
Extracts insights from large datasets
Powers modern AI-driven products