Machine Learning is a subset of artificial intelligence (AI) that focuses on the development of computer programs that can access data and use it to learn for themselves. The goal of machine learning is to enable computers to improve their performance on specific tasks through experience.
Key Concepts
Supervised Learning: This is a type of machine learning where the algorithm learns from a labeled dataset. The algorithm tries to learn a mapping from input to output.
Unsupervised Learning: In this type of machine learning, the algorithm is given data without explicit instructions on what to do with it. The algorithm tries to find structure in the data.
Reinforcement Learning: This is a type of machine learning where an agent learns to make decisions by performing actions in an environment to achieve a goal.
Applications
Machine learning is used in a variety of fields, including:
- Healthcare: Predicting patient outcomes, diagnosing diseases, and personalized medicine.
- Finance: Credit scoring, fraud detection, and algorithmic trading.
- Retail: Customer segmentation, recommendation systems, and demand forecasting.
Resources
For more information on machine learning, you can visit our Machine Learning Tutorial.