📊 Machine Learning (ML)

Machine Learning (ML) is a branch of Artificial Intelligence (AI) that enables computers to learn from data and improve performance without being explicitly programmed.

Instead of hard-coded rules, ML systems find patterns in data and make predictions or decisions.

🔹 Key Types of Machine Learning

1. Supervised Learning

The model is trained on labeled data (input + correct output).

Learns the mapping from inputs to outputs.

💡 Examples:

Predicting house prices (input: size, location → output: price).

Spam email detection (input: email text → output: spam/not spam).

2. Unsupervised Learning

The model works with unlabeled data (only input, no output).

Finds hidden patterns, clusters, or structures.

💡 Examples:

Customer segmentation in marketing.

Grouping similar news articles.

3. Reinforcement Learning (RL)

The model learns by interacting with an environment and receiving rewards or penalties.

Goal: maximize long-term reward.

💡 Examples:

Training robots to walk.

Self-driving cars learning traffic rules.

🔹 Machine Learning Workflow

Data Collection – Gather raw data.

Data Preprocessing – Clean, transform, and prepare the data.

Model Selection – Choose the right algorithm (e.g., Decision Tree, Neural Network).

Training – Teach the model using training data.

Evaluation – Test with new (unseen) data to check accuracy.

Deployment – Use the trained model in real-world applications.

Monitoring & Improvement – Update with new data for better performance.

🔹 Popular ML Algorithms

Linear Regression → Predict continuous values (e.g., stock prices).

Logistic Regression → Binary classification (e.g., yes/no decisions).

Decision Trees & Random Forests → Classification & regression.

K-Means Clustering → Grouping similar items.

Neural Networks → Power deep learning models.

🔹 Applications of Machine Learning

Healthcare → Disease prediction, medical imaging.

Finance → Fraud detection, credit scoring.

Retail → Recommendation systems (like Amazon, Netflix).

Transportation → Self-driving cars.

Marketing → Customer segmentation, targeted ads.

✅ In summary:

Machine Learning = Teaching computers to learn from data → predict, classify, or take decisions without explicit programming.

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