What Is Machine Learning?
Machine Learning is a branch of Artificial Intelligence (AI) that enables computers to learn from data and improve performance without being explicitly programmed. Instead of following fixed rules, machine learning systems analyze patterns, make predictions, and take decisions based on data.
In simple terms, machine learning allows machines to think and learn like humans by using data, algorithms, and statistical models. Popular examples of machine learning include recommendation systems (Netflix, Amazon), spam email detection, face recognition, and self-driving cars.
Understanding what is machine learning is the first step toward building intelligent applications in today’s data-driven world.
Machine Learning Types
There are different machine learning types, each used for specific problem-solving tasks. A quality Machine Learning Course in Dehradun covers all major machine learning types in detail.
- Supervised Learning
Supervised learning is one of the most common machine learning types. In this method, the model is trained using labeled data. It is widely used for classification and prediction tasks such as spam detection, price prediction, and disease diagnosis.
- Unsupervised Learning
Unsupervised learning works with unlabeled data. The system identifies hidden patterns and relationships in the data. Common applications include customer segmentation, clustering, and market analysis.
- Semi-Supervised Learning
This is a combination of supervised and unsupervised learning. It uses a small amount of labeled data along with a large amount of unlabeled data, making it cost-effective and efficient.
- Reinforcement Learning
Reinforcement learning is an advanced machine learning type where the model learns by interacting with an environment and receiving rewards or penalties. It is widely used in robotics, gaming, and automation systems.
Learning these machine learning types helps students understand how real-world AI systems work.
