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School / Prep
ENSTBB
Internal code
BT8PROG4
Description
Understand how gradient descent works and how to apply it. Combine machine learning approaches with boosting algorithms and optimize the performance of the resulting models.
Teaching hours
- CIIntegrated Courses10h
- CMLectures2h
Mandatory prerequisites
Programming and Artificial Intelligence III
Further information
Machine learning: in depth. Gradient descent for machine learning, boosting and combinations of multiple approaches. Case study applications.
Assessment of knowledge
Initial assessment / Main session
| Type of assessment | Nature of assessment | Duration (in minutes) | Number of tests | Evaluation coefficient | Eliminatory evaluation mark | Remarks |
|---|---|---|---|---|---|---|
| Integral Continuous Control | Continuous control | 1 |
Second chance / Catch-up session
| Type of assessment | Nature of assessment | Duration (in minutes) | Number of tests | Evaluation coefficient | Eliminatory evaluation mark | Remarks |
|---|---|---|---|---|---|---|
| Integral Continuous Control | Continuous control | 1 |