Data methods

1. Deep learning

1.1. Artificial neural networks

1.2. Convolutional neural network

2. Regression

2.1. Linear regression

2.2. Logistic regression

3. Bayesian methods

4. State space model (time-series)

5. Object detection and image segmentation

6. Survival analysis

7. Dynamic time wrapping

8. Gaussian model

9. Language models

9.1. Text mining

9.2. Sentiment analysis

9.3. Cognitive modelling

9.4. Natural language processing

10. Association rules

11. Classification

11.1. Support vector machines

11.2. Decision tree

11.3. Random forest

12. Large language models

13. Agent based modelling

14. Reinforcement learning

15. Generalised addictive modelling

16. Clustering

16.1. K-means clustering

16.2. Hierarchical clustering

16.3. Gassian Mixture Model

17. Gradient boosting