SophI.A Master Classes 2019

Telecom Valley

2 sessions of 4 free Master Classes in parallel (2h30 each one).

Université de Nice Sophia Antipolis

2 sessions of 4 free Master Classes in parallel (2h30 each one), one in the morning (beginning at 10:00am) and one in the afternoon (beginning at 2:00pm).

The content of the 2 sessions is similar in the morning and the afternoon.You can choose 1 topic in the morning and another in the afternoon from the following 4 topics :<ul><li>Modeling &amp; tooling for non AI Experts by IBM</li></ul>Speakers : Vincent BERAUDIER, Team Lead for the Continuous Learning servicePhilippe GREGOIRE, Partners Technical Enablement Europe – Data Science and IoTAmélie HOCQUETTE, Program Director, Development, Decision OptimizationJerome JOUBERT, Senior Offering ManagerIn this hands-on session you will learn how to combine several AI technologies to address an end-to-end scenario. You will understand how machine learning, prescriptive AI and decision optimization can be streamlined to solve a real-life problem. More importantly, you will understand that you don’t need to be an AI expert to be successful. In this scenario, you will be working for a fictional telecom operator. Based on historical data, you will have to identify potential customers that are likely to cancel their subscription. For each one, you will determine the best offer that this customer cannot miss. Finally, you will find the best course of action, and schedule personalized customer calls based on your operational constraints.<ul><li>Projet Wasabi : rendre la musique accessible à tous by UCA</li></ul>Speaker : Michel BUFFA, Computer Engineering Teacher &amp; Researcher Try to experiment by yourself the Wasabi roject with Michel BUFFA. Bring your instrument and join this technological &amp; musical master class !<ul><li>Rasa by NPXLAB</li></ul>Speakers : Raoul DO NASCIMENTO, CEO &amp; Founder Arij MELLITINPXLAB use natural language processing using Rasa in its Rheveo product (HR software market for mid size to major companies). We will introduce the HR context and tools used in the market with HR solutions and current trends. During the session we will demonstrate the use of Rasa with few examples. We will use an environment created beforehand and try a few use cases to better understand how to setup a bot in your company. At the end we will discuss the use of AI in the context of HR and recall few ethical principles we apply to ourselves and our customers.<ul><li>Small data AI on embedded platforms by MYDATAMODELS</li></ul>Speaker : Carlo FANARA, Lead Data ScientistSince its foundation MyDataModels (MDM), has been using small data, highlighting how these ‘democratizes’ the field, allowing Domain Experts and professionals to access machine learning results in an unprecedented way. Machine Learning (ML) models can be generated in several ways, including artificial neural network (ANN) and deep learning (DL), but also – like in the case of MDM – using Genetic Algorithms (GA). Whilst the latter may suffer in terms of execution time, ways to define and assess early convergence can be found. This is one of the major efforts currently undertaken at MDM; and it is worth, because MDM GA’s provide mathematical formulae which include the variables from the original dataset. Thus, models become explainable. A model trained on a machine can be loaded on an edge device, where it is used to infer novel results. In this Masterclass, MDM will present a few demos of inference achieved by the models on different architectures. After an introduction on the subject by our partners at INRIA, models will be first generated on data provided by the users; and then applied on selected consumer platforms (Raspberry Pi, Arduino).MDM will provide the entire development chain: first a demo of the model generation (training) onto a laptop computer, using data brought by the participants. As we focus on ‘small data’, we request the participants not to exceed 1MB size (in csv format). Thereafter, the participants will be able to follow all the steps of the creation, uploading and execution of the trained model, and able to appreciate the prediction capability on a real device, all within the time of the demonstration.

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SophI.A Master Classes 2019

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