About this document
Understanding Well-Posed Problems in ML by swetha sai is a document available to read on EtoBox.
Machine learning (ML) aims to develop systems that learn from data and improve autonomously, marking a progression towards artificial intelligence. A well-posed problem in ML requires a clear objective, sufficient data for unique mapping, and stability in output with input changes, while challenges like overfitting and underfitting can arise from data issues. Techniques such as regularization and cross-validation are employed to stabilize learning and ensure well-posed problems.
- Author
- swetha sai
- Language
- EN