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.

Regression Classification Ensemble

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.

Clustering Association Dimensionality Reduction

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.

Time Series Components Exponential Smoothing ARIMA LSTM
Work in Progress
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