DESCRIPTION
Objectives:
The objective of this MasterCamp© is to introduce recent machine learning and deep learning techniques to process massive data for connected objects, with applications in computer vision and time series.
Program:
• Know how to train machine learning algorithms
• Know how to train deep learning algorithms such as CNN and LSTM for supervised classification
• Know how to implement unsupervised learning algorithms
• Know how to train deep learning algorithms for regression
• Know the principles of feature extraction and finetuning on existing networks
• Know and manipulate high-dimensional data reduction and visualization methods (LLE, Laplacian EigenMaps, T-SNE)
• Robustness and vulnerability of deep learning algorithms and how to ensure their
operational safety
• Know how to train à GAN type method (Generative Adversarial Network) for the creation of data.
REQUIREMENTS
- Know how to use Python
- A computer with internet
- English/French language
WHO IS THIS COURSE FOR
This MasterCamp© aims to help students, researchers and engineers.
THIS MasterCamp™ INCLUDES
- Downloadable resources
- TD Exercises
- Practical work in Python with Jupyter Notebook
- Training certificates
- Access on mobile and PC
- Slide courses
WHAT YOU WILL LEARN IN THIS MasterCamp™
- Being able to implement artificial intelligence algorithms for processing large masses of data.
- We will be concentrated on emerging approaches to learning methods (based on neural networks, for example) to prepare for the most complex situations.
- Understand how machine learning algorithms work
- Manipulate Python code to implement deep learning solutions
- Well document AI solutions
My Story
I received the diploma degree in Electrical Engineering from the “Ecole Supérieure d’Electricité (Supélec), Gif-sur-Yvette”, France, in 2000. I also received the DEA degree and the Ph.D. in signal processing from the University of Paris-Sud, Orsay, France, in 2000 and 2003 respectively. Between 2003 and 2004, i was postdoctoral researcher at IRCCyN, “Institut de Recherches en Communications et Cybernétiques de Nantes”. I was always passionate about science and technology. I have spent short periods as visiting scientist at the Brain Science Institute, RIKEN, Japan and Olin Neuropsychiatry Research Center at the Institute of Living in the USA. My passion about my field has motivated me to co-found 2 start-ups: Damavan Imaging in 2014 (nuclear imaging) and Aquilae in 2017 (Artificial Intelligence for vision analytics).
Where I’ve Worked
2021 - Now
Deputy director of LIST3N lab and team leader of M2S group.
2016 and 2020
Manager of LM2S Lab
2014 and 2017
C-founder of 2 start-ups Damavan Imaging in 2014 (nuclear imaging) and Aquilae in 2017 (Artificial Intelligence for vision analytics).
2005 and 2009
Associate professor
Skills you will gain
Data sciences and AI
- Data Science
- Deep Learning
- Machine Learning
- Big Data
- Data Mining
- Github
- Python Programming
- Jupyter notebooks
- Rstudio
- Methodology
- CRISP-DM
- Data Analysis
