20 methods of the data scientist and the mathematics behind them¶
Contents¶
- 1. Relational databases and their algorithms
- 2. Static and dynamic summary statistics
- 3. Analysis of univariate distributions
- 4. Analysis of multivariate distributions
- 5. Analysis of covariance and correlation
- 6. Finding the best line through a cloud of points
- 7. General least squares
- 8. Logistic regression and GLM
- 9. Clustering (k-means)
- 10. PCA and data-reduction
- 11. Gradient Descent
- 12. Kalman Filtering
- 13. Textual and categorical classification
- 14. Convolutions filtering
- 15. Fourier analysis of signals
- 16. Deep neural networks
- 17. Data compression
- 18. Dynamic programming and reinforcement learning
- 19. Linear programming
- 20. Scheduling, Knapsack and Integer programming