Algorithms for Data Science
1. Supervised
Supervised learning contains machine learning algorithms in which models are trained using labeled data. Model is trained with input features and output, using this learning, model will predict for new input examples.
2. Unsupervised
Unsupervised learning algorithms uses non-classified and unlabeled data. The goal of the algorithm (model) is to find similarities or patterns in the data by its own.
3. Time Series
Time series is a branch of supervised learning. Observations in measured chronological sequence, often in regular interval. Time series models do short/long term forecasting.