Machine learning is about programming computers to optimize a function based on previous experience. The computer is given empirical data to analyze and build a model function that can predict the output on unseen data that it might encounter in the real world. The computer builds a function based on the parameters and the empirical data supplied to it. This function evolves as more empirical data is given or when there is a change in the data characteristics. When this function is applied on unseen data at a later point, it predicts the output based on the model function. The empirical data supplied to learn this function is termed as training data.
The following are the kinds of machine learning algorithms:
- Supervised learning ...