About this document
Supervised Learning in AI Applications by Hoài Hân Nguyễn is a document available to read on EtoBox.
The document discusses supervised learning in artificial intelligence, focusing on its two main types: regression and classification, which utilize labeled training data to make predictions. It explains linear regression, including its assumptions, loss functions, and methods for minimizing errors, such as the least squares method and gradient descent. Additionally, it addresses model evaluation concepts like overfitting, underfitting, and the bias-variance trade-off.
- Author
- Hoài Hân Nguyễn
- Language
- EN