What is Machine Learning? Types, Overfitting, Hyperparameters, Feature Engineering, Model prediction
Machine learning (ML) is a subset of artificial intelligence (AI) that gives computers the ability to learn without being explicitly programmed. Instead, ML algorithms learn from data and improve their performance over time.
There are three main types of machine learning:
Supervised learning: In supervised learning, the computer is given a set of labeled data. The labels tell the computer what the correct output should be for a given input. The computer then learns to map inputs to outputs based on the labeled data.
Unsupervised learning: In unsupervised learning, the computer is not given any labeled data. The computer must learn to find patterns in the data on its own. This type of learning is often used for tasks such as clustering and dimensionality reduction.
Reinforcement learning: In reinforcement learning, the computer is given a reward signal for taking actions that lead to desired outcomes. The computer then learns to take actions that maximize the reward signal. This type of learning is often used for tasks such as playing games and controlling robots.