Phelma Formation 2022

Introduction to Machine learning and Deep learning - 5PMBMLD0

  • Number of hours

    • Lectures 0
    • Projects 0
    • Tutorials 16.0
    • Internship 0
    • Laboratory works 12.0
    • Written tests 0

    ECTS

    ECTS 2.0

Goal(s)

Learn some basic algorithms for Machine Learning and deep learning
Learn to design the right Machine Learning method according to a given dataset
Learn to evaluate the performances on a Machine Learning system

Contact Alice CAPLIER

Content(s)

0. Introduction to deep learning
1. K-NN and Bayesian classification
2. Linear regression
3. Logistic Regression
4. SVM Classifier / Principal Component Analysis / Kmeans clustering
5. Neural Networks
6. Convolutional Neural Networks
7. Generative Neural Networks
8. Recurrent Neural Networks



Prerequisites

Python language MANDATORY
1st year mathematics course

Test

Semester 9 - The exam is given in english only 

Continuous assessment
Reports + MCQ



En session 1
Pour le cours : Contrôle continu : QCMs + rapports
Pour le BE : contrôle continu : rapport
N1 = Note finale session 1 = 50% moyenne du CC cours + 50% note rapport de BE

En session 2
Rapport sur un mini projet
N2 = note du rapport

Les modalités sont les mêmes en présentiel et en distanciel

Additional Information

This course brings 3.0 ECTS to students in UE Engineering ( SàC SCOG )

Semester 9 - This course is given in english only EN
Course list
Curriculum->Double-Diploma Engineer/Master->Semester 9
Curriculum->BIOMED->Semester 9