20 methods of the data scientist and the mathematics behind them
latest
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
Use in data science:
Applicable mathematics:
20 methods of the data scientist and the mathematics behind them
Docs
»
20. Scheduling, Knapsack and Integer programming
Edit on GitHub
20. Scheduling, Knapsack and Integer programming
¶
Use in data science:
¶
Variable selection
Large scale operational optimization
Discrete optimization and control problems
Applicable mathematics:
¶
Linear algebra
Discrete mathematics and combinatorics
Read the Docs
v: latest
Versions
latest
Downloads
pdf
htmlzip
epub
On Read the Docs
Project Home
Builds
Free document hosting provided by
Read the Docs
.