Data Science Nancy

Three Data Science researchers and practitioners will share in a few hours their experience in our Data Science Nancy Meetup #2 Atelier Numérique Nancy. Andra Sonea will speak about localized interventions for supporting financially disempowered in situations of reduced access to physical and digital financial services in two regions in UK. Muzzolon will share her experience on Data Science and AI projects she has been working on in Tribe - IT Partners. Lesage will present us a piece of his research about recommendation system for car insurance. https://www.meetup.com/Data-Science-Nancy/events/265680549/

Happy to announce that for the Data Science Nancy Meetup #2 we will have Marie MUZZOLON, currently working as an AI consultant with IT Partners, Strasbourg. With a Master in Mathematical Engineering and Computer Tools, from Faculty of Sciences and Technologies, Nancy, Marie will share her experience about working with AI and data processing and how is to advise clients on their projects to use AI for their business needs. Marie is also involved in an internal R&D project she will speak about. Join us at Google Ateliers Numeriques Nancy, on Nov 12, 18.30. Hurry up to register! Share if you care! https://lnkd.in/eBmkVB6

Real Life Data Science. New Trends in Business Tue, Nov 12, 2019, 6:30 PM: Agenda:[masked] Welcome and networking[masked] Presentations and discussions[masked] NetworkingShort description:Two Data Science practitioners will share their experience.

Two Data Science practitioners will share their experience Science Nancy Meetup , on Nov 12, 18.30. Sonea will speak about localized interventions for supporting financially disempowered in situations of reduced access to physical and digital financial services in two regions in UK. Marie MUZZOLON will share her experience on Data Science and IA projects she has been working on.

Real Life Data Science. New Trends in Business Tue, Nov 12, 2019, 6:30 PM: Agenda:[masked] Welcome and networking[masked] Presentations and discussions[masked] NetworkingShort description:Two Data Science practitioners will share their experience.

" Data Science for Finance: supporting financially disempowered in
situations of reduced access to physical and digital financial services" with Andra Sonea - a new meetup of Data Science Nancy is announced for November Google Atelier Numérique Nancy, 19.00-21.00. Andra is a Consultant and Architect in Financial Services, and also PhD candidate Institute for the Science of Cities, of Warwick. Stay tuned!!! More details to come. Join Data Science Nancy Meetup to stay informed https://www.meetup.com/Data-Science-Nancy/

Postdoc position opened at IECL/GeoRessources in Nancy.

postdocPositionIECLGeoRessources.pdf

PhD position available at IECL - Université de Lorraine (Nancy):

"Simultaneous model and pattern learning in spatial data. Application to the statistical analysis of the mixing dynamics of geological fluids." https://drive.google.com/file/d/1TFsyQEO0uWam6hH6YYe1TajhJg5l7K9S/view?fbclid=IwAR28iSu8cDQb7ia9DstI7E6kXsaQ6l01pubepaCvVNxTmHOOjiNW3xdYVF4

phdSubjectStoicaDeaconuRichard.pdf

A few ideas from the first Data Science Nancy Meetup

1) Radu Stoica, Professor at Lorraine University and Researcher with "Elie Cartan" Institute of Lorraine

• spatial data : data sets with two components, position and characteristics;
• application domains : image analysis, environmental sciences, astronomy, industry;
• question one data scientist is interested to answer: "What is the pattern hidden in the data ?"
• the key hypothesis is: the pattern is a complex entity made of simple objects that interact;
• the answer may be brought to answer it by stochastic modelling shall be used;
• is about using prior knowledge of the studied phenomenon in order to build the models;

Examples of applications:

• animal epidemiology: sub-clinical mastitis for dairy herds in France;
• image analysis: road and hydrographic networks;
• cosmology: spatial distribution of galaxies;
• industry : spatio-temporal distribution of leaks on a water distribution network;

Note: things become more complex when time variable occurs;

Scientific trends in Data Science:

• contribute to answer fundamental scientific questions;
• transfer the developed knowledge to students and to social actors;
• be aware of the general impact: social, environmental, ethical;
• propose real win-win partnerships;
Question: what is the pattern hidden in the data? Writing a computer program to describe the color distribution and the horse silhouette is not a trivial challenge.
Figure: Robert Delaunay: Paysage nocturne (le fiacre). Centre Pompidou Metz.

2) Marianne Clausel, Professor with Lorraine University and Researcher with Elie Cartan Institute of Lorraine

• Textual data are at the core of AI;

Analysing textual data might be a challenging given the fact that:
• the format is not predefined;
• there is a specific vocabulary;
• may evolve in time (for a blog);
• there might be potential interdependencies inside and outside the document itself;

The question arising is how to stock, to classify and to analyse them;

A few examples of questions:
• creation of an interactive map allowing to visualize patents?
• can one predict the evolution of financial markets via social networks? Using sentiment analysis;
• analysis of the correspondence between the employees;
• analyzing health tweets: tweets, human sensors;
• can we anticipate the spread of diseases?

Julien Trombini, co-founder and President of Two-i SAS, a video content analytics start-up, and researcher with Elie Cartan Institute of Lorraine.

Several ideas on Big Data:

4 Vs of Data: Volume (Scale of Data), Velocity (Analysis of Streaming Data), Variety and Veracity (Uncertainty of Data);

Machine Learning techniques:
• Supervised learning: classification and regression;
• Unsupervised learning: clustering, dimensionality reduction, and association rule learning.

Photos from the Meetup on Trends and Perspectives in Data Science, Nov 28, 2018

Julien Trombini speaking about storing data and Volume, Velocity and Veracity (uncertainty of data), Variety of Data.

Marianne Clausel talking about nanoobjects.

Stoica talking about spatial data analysis Data Science Nancy Meetup. Data about galaxies distribution, matching LinkedIn profiles, spread of Mastitis in France - are just a few topics approached.