Machine learning is a subset of artificial intelligence that focuses on the development of algorithms that can learn from and make predictions or decisions based on data. Here are some key concepts in machine learning:
- Supervised Learning: This is where the model is trained on labeled data, meaning each data point is associated with an output label.
- Example: A spam filter that learns to classify emails as spam or not spam based on the content.
- Unsupervised Learning: Here, the model is trained on data without labeled responses. The goal is to find patterns and insights in the data.
- Example: Clustering similar customers into groups for targeted marketing.
- Reinforcement Learning: This type of learning involves an agent that learns to make decisions by performing actions in an environment to achieve a goal.
- Example: Training a robot to navigate a maze.
Machine Learning Process
For more information on machine learning techniques and applications, check out our Machine Learning Tutorial.