👋 Welcome to Notion!

🔍 Introduction

Machine Learning (ML) has become one of the most transformative technologies of the 21st century. As a subset of artificial intelligence (AI), it empowers systems to learn from data and adapt without explicit programming. In 2025, Machine Learning continues to reshape industries by enhancing automation, decision-making, and predictive accuracy. Whether you're a tech enthusiast, business leader, or aspiring data scientist, understanding ML is essential in today's data-driven world.

📘 What is Machine Learning?

Machine Learning refers to the use of algorithms that analyze data, learn from patterns, and make informed decisions with minimal human intervention. Instead of hardcoding rules, ML models improve performance as they process more data, becoming smarter over time.

🧩 Types of Machine Learning

1. Supervised Learning

Uses labeled datasets to train models. It's ideal for classification (e.g., spam detection) and regression (e.g., house price prediction).

2. Unsupervised Learning

Identifies hidden patterns in unlabeled data. Commonly used for clustering (e.g., customer segmentation) and association (e.g., market basket analysis).

3. Semi-Supervised Learning

A blend of labeled and unlabeled data. It increases model accuracy when labeled data is scarce.

4. Reinforcement Learning

Models learn by trial and error, receiving feedback in the form of rewards or penalties—widely used in robotics and gaming.

⚙️ How Does Machine Learning Work?

1. Data Collection: Gathering structured or unstructured data.
2. Data Preparation: Cleaning, normalizing, and transforming data.
3. Model Selection: Choosing the right algorithm (e.g., decision tree, neural network).
4. Training: Feeding data to help the model learn.