Machine learning is a field of artificial intelligence that gives computers the ability to learn and improve from experience without being explicitly programmed. It's a subset of AI that focuses on the development of algorithms that can learn from and make predictions or decisions based on data.
Key Concepts
- Supervised Learning: This is a type of machine learning where the algorithm learns from a labeled dataset. The goal is to learn a mapping from input to output variables.
- Unsupervised Learning: In this type, the algorithm is given data without explicit instructions on what to do with it. The goal is to find structure in the data.
- Reinforcement Learning: This is a type of learning where an agent learns to make decisions by performing actions and receiving rewards or penalties.
Applications
Machine learning is used in various fields such as:
- Healthcare: Predicting patient outcomes, diagnosing diseases.
- Finance: Credit scoring, algorithmic trading.
- Retail: Personalized recommendations, demand forecasting.
Resources
For further reading, check out our Introduction to Machine Learning.
Machine Learning Diagram