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Navigable Slide Index

1. Introduction
2. Motivation (1)
3. Motivation (2)
4. Machine learning
5. Machine learning- three main decisions
6. Machine learning categories
7. Data representation
8. Learning success
9. Learning a model
10. Overfitting (1)
11. Overfitting (2)
12. Complexity control by design
13. Supervised machine learning
14. Prerequisites and scenarios (1)
15. Quantitative Structure-Activity Relationship (1)
16. Quantitative Structure-Activity Relationship (2)
17. Molecular descriptors
18. A descriptor based QSAR model
19. A descriptor based QSAR model- an example
20. Optimal machine learning
21. Data representation in supervised learning
22. Vectorial data representation
23. Structured data representation
24. Learning objective
25. Machine learning evaluation
26. Machine learning evaluation- pitfalls
27. Unsupervised machine learning
28. Prerequisites and scenarios (2)
29. Unsupervised machine learning- subcategories
30. Clustering
31. Distribution estimation
32. Virtual screening (1)
33. Virtual screening (2)
34. VS performance estimation (1)
35. VS performance estimation (2)
36. Take home message
37. Thank you

Topics Covered

• Data representation in machine learning
• Learning success models
• Overfitting
• Complexity control by design
• Supervised & Unsupervised machine learning
• Quantitative Structure-Activity Relationship (QSAR)
• Molecular descriptors
• A descriptor based QSAR model
• Choosing a learning objective
• Machine learning evaluation
• Clustering
• Distribution estimation
• Virtual screening (VS)
• VS performance estimation

Links

Series:

• Introduction to Cheminformatics

Categories:

• Methods

Talk Citation

Fechner, N. (2011, May 31). Introduction to machine learning and its application in chemistry [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved November 21, 2024, from https://doi.org/10.69645/CMMQ8229.
Export Citation (RIS)

Publication History

• Published on May 31, 2011

Financial Disclosures

• Dr. Nikolas Fechner has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.