Here are some relevant information related to the Machine Learning lectures. 

Content:

[L1] Lecture 1: Introduction to machine learning: 1.5h (download handout)

[L2] Lecture 2: Naïve Bayes classifier: 1.5h (download handout)

[L3] Lecture 3: Gaussian distributions: 1.5h  (download handout)

[L4] Lecture 4: to be defined Non parametric classifiers: 1.5h (download handout)

 

Two practicals are associated to lecture:

[P1]: Practical 1 : (related to L1 and L2): 3h (download)

[P2]: Practical 2:  Estimation of 3D distance on faces using Machine Learning technics : 3h (download)

 

Here is a tuto. for connecting to the VM Mecatronique (download)

Attachments

studentsML P .zip [5.2Mb]

Uploaded Thursday, 13 September 2018 by Super Utilisateur

201809180420 ML .pdf [3.8Mb]

Uploaded 4 weeks ago. by Super Utilisateur

TD .pdf [966.01Kb]

Uploaded 4 weeks ago. by Super Utilisateur

201809180505 ML handout.pdf [5.17Mb]

Uploaded 4 weeks ago. by Super Utilisateur

201809180507 ML .pdf [4.39Mb]

Uploaded 4 weeks ago. by Super Utilisateur

201810011210 ML .pdf [3.82Mb]

Uploaded 2 weeks ago. by Super Utilisateur

201810011213 studentsML P .zip [43.33Mb]

Uploaded 2 weeks ago. by Super Utilisateur