Model Selection for Optimal Prediction in Statistical Learning - Part 2 / 2 | AISC

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Canada LLMs Explained - Aggregate Intellect - AI.SCIENCE
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Published on ● Video Link: https://www.youtube.com/watch?v=Slx7Dt4JmIk


Duration: 1:24:26
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12

Speaker(s): Ernst Fokoue
Facilitator(s): Nour Fahmy


Speaker(s): Ernest Fokoue
Facilitator(s): Nour Fahmy

Find the recording, slides, and more info at https://ai.science/e/model-selection-for-optimal-prediction-in-statistical-learning-part-2-2--2FEr8EoWBttpPX6RSVM0

Motivation / Abstract
Professor Ernest will walk us through a statistical framework for model selection. His emphasis on investigating underlying probabilistic phenomenon is crucial to a methodical understanding of how the data behaves. This consistency will be shown through every step of the modelling journey; choosing the most appropriate metric for model accuracy and likelihood function, aggregation techniques, and how to evaluate model performance from a probabilistic and statistical perspective.

What was discussed?
- Choosing appropriate metrics for model accuracy
- Choosing appropriate likelihood functions
- Aggregation techniques
- Model performance evaluation
... But from a probabilistic perspective

What are the key takeaways?


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