Taming randomness in ML models with hypothesis testing and marimo

In 'Taming randomness in ML models with hypothesis testing and marimo,' Davide Eynard discusses how randomness affects ML model behavior and the evaluation of their performance. The author introduces hypothesis testing with a hands-on marimo app, explaining why understanding statistical testing is crucial when comparing different ML models. The article emphasizes the significance of hypothesis testing in determining the best-performing machine in terms of stochastic outcomes.

• Randomness impacts ML model evaluation.
• Evaluation complexity goes beyond metrics.
• Dice throwing explains hypothesis testing.
• Marimo app teaches statistical testing.
• Statistics book insights remain relevant.