Coordinated by: Michel Riveill, PR Université Côte d'Azur
SCHEDULEFORMAT
Classroom
LOCATION
Campus SophiaTech, Lucioles
Prerequisites
- Scientific Bachelor
- Python programming
- Prerequisites and main concepts of Minor AI Introduction
CAPACITY
24 students
ABOUT THIS MINOR
This minor is also open to students from the SPECTRUM and LIFE graduate schools.
- Summary
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The course on deep learning is fundamental. It will help you understand the capabilities, challenges and implications of deep learning and prepare you to participate in the development of cutting-edge AI technologies.
LEARNING OUTCOMES
- Know the principles of Deep Learning (neural network)
- Know how to build models based on neural networks to process structured data, images or time series
In this course, you will build and train neural network architectures such as convolutional neural networks or recurrent neural networks, and most importantly, you will learn how to improve them with strategies such as Dropout, BatchNorm, different initialization strategies. Theoretical concepts and their industrial applications using Python and TensorFlow will be implemented on object recognition or natural language processing problems.
Find out more about this minor on Moodle...(course's name "ADVANCED AI: ADVANCED MACHINE LEARNING AND DEEP LEARNING") - Lecturers
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- Diane Lingrand (PR Université Côte d'Azur, Polytech Nice Sophia, i3S)
- Michel Riveill (PR Université Côte d'Azur, Polytech Nice Sophia, i3S)
- Prerequisites
- If you do not practice Python on a daily basis,
- autoevaluate yourself to make sure you do have the prerequisites: http://www.i3s.unice.fr/~riveill/python/auto_eval.html
- review the tutorial: https://www.programiz.com/python-programming/tutorial especially the chapters :
- Python Introduction
- Python Flow Control
- Python Functions
- Python Datatypes
- Python Files
- train yourself (Learn the Basics, Data Science Tutorials, Advanced Tutorials) from the tutorial : https://www.learnpython.org/
- Bibliography
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- Statistics and Machine Learning in Python. Edouard Duchesnay, Tommy Löfstedt (presents Python language for machine learning)
- Python Machine Learning. Sebastian Raschka https://github.com/rasbt/python-machine-learning-book-3rd-edition)
- Hands-on machine learning with Scikit-Learn and TensorFlow: concepts, tools, and techniques to build intelligent. A. Géron. O’Reilly (practical)
- Data science : fondamentaux et études de cas: Machine learning avec Python et R. M. Lutz, E. Biernat. Editions Eyrolles (In French, introduction level but requires some maths background: https://elmoukrie.com/wp-content/uploads/2022/05/eric-biernat-michel-lutz-yann-lecun-data-science-_-fondamentaux-et-etudes-de-cas-_-machine-learning-avec-python-et-r-eyrolles-2015.pdf)
- Evaluation
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- The course is subject to continuous assessment. It is possible that certain sessions begin with an examination and that the practical work or lab will be assessed.
- 50% of the mark will be awarded on the basis of a short examination (at least one examination).
- 50% of the mark will be awarded on the assessment of practical work (at least one assessed practical task).
SCHEDULE FALL 2024
Mind the evaluation modalities and deadlines in the "Evaluation" tab above.
| Date | Time | Course's title | Lecturers | Place |
| 10/10/2024 | 9h00-12h30 | Deep learning - General principles | Michel Riveill | Campus SophiaTech, Lucioles, room 352 |
| 17/10/2024 | 9h00-12h30 | Multi-layers perceptron | Michel Riveill | Campus SophiaTech, Lucioles, room 352 |
| 24/10/2024 | 9h00-12h30 | Auto-Encoder and Latent Representation | Michel Riveill | Campus SophiaTech, Lucioles, room 352 |
| 31/10/2024 | No lecture | Break | - | - |
| 07/11/2024 | 9h00-12h30 | Recurrent Neural Network for time series | Michel Riveill | Campus SophiaTech, Lucioles, room 352 |
| 14/11/2024 | 9h00-12h30 | Convolutional Neural Network 1 | Diane Lingrand | Campus SophiaTech, Lucioles, room 352 |
| 21/11/2024 | 9h00-12h30 | Convolutional Neural Network 2 | Diane Lingrand | Campus SophiaTech, Lucioles, room 352 |
| 28/11/2024 | 9h00-12h30 | No lecture -SophIA Summit | Campus SophiaTech, Lucioles, room 352 | |
| 05/12/2024 | 9h00-12h30 | Object Detection | Diane Lingrand | Campus SophiaTech, Lucioles, room 352 |
| 12/12/2024 | 9h00-12h30 | Recomender Systems and Lab Presentation | Michel Riveill | Campus SophiaTech,Lucioles, room 352 |