K nearest neighbors (KNN) - explained | validation
![](https://i.ytimg.com/vi/ayfr6KN4Jd0/mqdefault.jpg)
10:56
Mahalanobis distance for classification | Machine Learning
![](https://i.ytimg.com/vi/MKy28gY8JYk/mqdefault.jpg)
10:45
KNN (classification), fonctionnement et métriques de calculs de distances
![](https://i.ytimg.com/vi/b6uHw7QW_n4/mqdefault.jpg)
8:01
What is the K-Nearest Neighbor (KNN) Algorithm?
![](https://i.ytimg.com/vi/3zbAsgCf1Sw/mqdefault.jpg)
30:49
The EM Algorithm Clearly Explained (Expectation-Maximization Algorithm)
![](https://i.ytimg.com/vi/oymtGlGdT-k/mqdefault.jpg)
49:42
Lecture 3 "k-nearest neighbors" -Cornell CS4780 SP17
![](https://i.ytimg.com/vi/NhGl3I6AKpM/mqdefault.jpg)
18:56
Validation techniques - explained with simple examples (Hold-out, cross-validation, LOOCV)
![](https://i.ytimg.com/vi/dz8imS1vwIM/mqdefault.jpg)
22:11
PCA : the basics - explained super simple
![](https://i.ytimg.com/vi/htnZp__02qw/mqdefault.jpg)
12:20