Navigation menu

m1p.org

Course syllabus

From m1p.org
Revision as of 19:30, 6 March 2023 by Wiki (talk | contribs) (→‎Course Syllabi)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

Below are listed the course syllabi on Data Science topics.

Course Syllabi

  1. My first scientific paper
  2. Bayesian model selection
  3. Fundamental theorems of Machine Learning
  4. Mathematical forecasting
  5. Structure learning and forecasting
  6. Bayesian multimodeling
  7. Introduction to Machine Learning
  8. Machine Learning
  9. Generative deep learning
  10. Applied regression analysis
  11. Neural architecture search
  12. Big data analysis
  13. Mathematics of decision making
  14. Data Mining in Business Analytics
Retrieved from ‘https://m1p.org/index.php?title=Course_syllabus&oldid=1203’
Edit
  • Login / Create Account