CS231n: Convolutional Neural Networks for Visual Recognition
Stanford, , Prof. Fei-Fei Li
Updated On 02 Feb, 19
Stanford, , Prof. Fei-Fei Li
Updated On 02 Feb, 19
4.1 ( 11 )
Lecture 2 formalizes the problem of image classification. We discuss the inherent difficulties of image classification, and introduce data-driven approaches. We discuss two simple data-driven image classification algorithms: K-Nearest Neighbors and Linear Classifiers, and introduce the concepts of hyperparameters and cross-validation.
Keywords: Image classification, K-Nearest Neighbor, distance metrics, hyperparameters, cross-validation, linear classifiers
Slides:
http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture2.pdf
Sam
Sep 12, 2018
Excellent course helped me understand topic that i couldn't while attendinfg my college.
Dembe
March 29, 2019
Great course. Thank you very much.