General Engineering Program
| General Data | ||||
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| Academic program | General Engineering Program | :
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| Type d'EC | Classes (LIIAem08EMachineLearning) | |||
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Status :
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Period :
ACADEMIC SEMESTER |
Education language :
French |
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| Learning Outcomes |
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| The theme of the DATA course in digital coloring is machine learning. The goal is to understand the issues and initial concepts of machine learning. Skills: - Understand conceptual definitions - Understand mathematical definitions - Implement these definitions on simple examples - Implement on a complex example - Analyze the results and suggest improvements - Team working |
| Content |
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| The course plan is as follows: - Linear regression and Gradient Descent - Logistic regression - Data: learning base vs test base - Over and under learning - Meta parameters - Perceptron - Neural networks The course will be enhanced with many exercises. The second part of the course is carried out in the form of a project whose objective is to implement the concepts seen in the first part. It is about carrying out a machine learning process on a real basis and studying the avenues for improvement. |
| Pre-requisites / co-requisites |
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| - Basics of algorithms. - Python basics |
| Bibliography |
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| Machine Learning course - Andrew Ng - Coursera - Stanford - 2021. Online : https://fr.coursera.org/learn/machine-learning Vidéos 3Blue1Brown series - Saison 3 - 2021 : Online ; https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi Deep Learning With Python, François Chollet, Edition Manning, 2022 |
| Assessment(s) | |||
|---|---|---|---|
| N° | Nature | Coefficient | Observable objectives |
| 1 | Project | 1 | |
| 2 | Continuous Assessment | 1 | |