IDEAS ARTIFICIALES

Anatomy of an AI’s algorithm

Anatomy of an AI’s algorithm

Translation coming soon. In this entry, we shall explore, at different levels of difficulty, how ML algorithms adjust their parameters to solve problems. We shall see that, at its core, it all comes down to an error minimisation problem.

Translation comming soon, for original text in spanish please check: Anatomía de un algoritmo de IA

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HERRAMIENTA

DeepSeek R1

PROMPTS

- Generate Python code to adjust the parameters of a logistic regression–based classifier created to solve a classification problem of oranges and tangerines. We will use weight and diameter as features. The data must present a 7% overlap between the classes. Include a confusion matrix to evaluate the model.