Machine learning algorithms are the heart of artificial intelligence, enabling systems to learn from data and make decisions or predictions. Here are some commonly used machine learning algorithms:
Supervised Learning
- Linear Regression: A simple linear model that predicts a continuous value.
- Logistic Regression: Used for binary classification problems.
- Support Vector Machines (SVM): A powerful classifier that finds the best hyperplane to separate data points.
- Neural Networks: Deep learning models that can learn complex patterns in data.
Unsupervised Learning
- K-Means Clustering: Groups data points into K clusters.
- Principal Component Analysis (PCA): Reduces the dimensionality of data by transforming it into a set of principal components.
- Association Rules: Finds patterns and relationships in large databases.
Reinforcement Learning
- Q-Learning: An algorithm that learns the best actions to take in an environment.
- Policy Gradient: A method that learns a policy directly from the gradients of the expected rewards.
For more information about machine learning algorithms, you can check out our Machine Learning Basics guide.
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