Lecture
Machine Learning Basics
Description
This lecture covers the fundamentals of machine learning, starting with data collection and feature engineering, followed by model selection and evaluation using metrics like precision, recall, and F1-score. It also delves into the importance of feature normalization and the dangers of standardization. The instructor emphasizes the significance of choosing the right model and hyperparameters, as well as the evaluation of classifiers through techniques like cross-validation and ROC analysis.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.