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Applied Math with Python - Home Applied Math with Python - Home
  • Applied Math with Python

General Statistics

  • 1. General Statistics

General Probability

  • 2. General Probability

Time Series Analysis

  • 3. Time Series Analysis

Bayesian Analysis

  • 4. Bayesian Analysis

Stochastic Processes

  • 5. Stochastic Processes

Non-Parametric Statistics

  • 6. Non-Parametric Statistics

General Numerical Methods

  • 7. General Numerical Methods

Numerical Linear Algebra

  • 8. Numerical Linear Algebra

Optimization

  • 9. Optimization in Mathematics and Computer Science
  • 10. Linear Programming
  • 11. Gradient Descent

Ordinary Differential Equations

  • 12. Ordinary Differential Equations (ODEs)

Partial Differential Equations

  • 13. Partial Differential Equations (PDEs)

Classification Models in Machine Learning

  • 14. Classification Models in Machine Learning

Regression Models in Machine Learning

  • 15. Regression Models in Machine Learning

Deep Learning

  • 16. Deep Learning

Reinforcement Learning

  • 17. Reinforcement Learning

Clustering Theory

  • 18. Clustering Theory in Data Science

Dimensionality Reduction Techniques

  • 19. Dimensionality Reduction Techniques

Information Theory

  • 20. Information Theory

Graph Theory and Network Analysis

  • 21. Graph Theory and Network Analysis

Game Theory

  • 22. Game Theory

Fourier Analysis

  • 23. Fourier Analysis

Natural Language Processing

  • 24. Natural Language Processing

Generative Artificial Intelligence

  • 25. Generative Artificial Intelligence

Operations Research

  • 26. Operations Research

Scientific Computing

  • 27. Scientific Computing

Applications to Biology and Epidemiology

  • 28. Applications to Biology and Epidemiology

Applications to Finance

  • 29. Applications to Finance

Applications to Material Science and Physics

  • 30. Applications to Material Science and Physics
  • Repository
  • Open issue

Index

By Jimmy Calvo-Monge and Michael Abarca

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