Machine Learning: Full Guide
🤖 What Is Machine Learning?
Machine Learning (ML) is a branch of Artificial Intelligence that enables computers to learn from data and improve their performance over time without being explicitly programmed.
🧠 Types of Machine Learning
| Type | Description |
|---|---|
| Supervised Learning | Trains on labeled data to predict outcomes. |
| Unsupervised Learning | Finds hidden patterns in unlabeled data. |
| Reinforcement Learning | Learns by trial and error to maximize rewards. |
| Semi-Supervised Learning | Uses a small amount of labeled data with a large amount of unlabeled data. |
| Self-Supervised Learning | Generates its own labels from data. |
🔧 How Machine Learning Works
- Data Collection
- Data Preprocessing
- Feature Engineering
- Model Selection
- Training
- Evaluation
- Deployment
📚 Common Algorithms
- Linear Regression
- Logistic Regression
- Decision Trees
- Support Vector Machines (SVM)
- K-Means Clustering
- Neural Networks
🌍 Real-World Applications
- Healthcare
- Finance
- Retail
- Transportation
- Agriculture
⚠️ Challenges and Considerations
- Bias in Data
- Overfitting
- Interpretability
- Data Privacy