In this Seminar,  the student obtains a basic and broad overview of Machine Learning tools/methods, which are crucially used in several interesting use-cases in the frame  of Intelligent Transportation Systems. Furthers, he shall conduct a comprehensive literature review w.r.t. to selected topics or use-cases in the described context.Selected applications fields  of ITS in which Machine Learning (AI / Deep Learning) does play a very crucial role are:# Autonomous driving cars# Driver Monitoring Systems# Industry 4.0 in Transportation and Logistics# Cooperative intelligent transportation systems# Social networks impact in/for intelligent mobility systems# Traffic Lights  Assistance systems# Analysis of the potential synergy between Electric Vehicles and Smart Electric Grids

GLOBAL PLAN:###########1) Kick-Off Meeting (at Semester begin): introductory presentation,  topics selection by the student, brief overview of related papers and documents.2) Intermediate Presentations (weekly): here, students present their mini-seminars outcomes. A related feedback is provided.3) Final presentations: second or last week  June. 

(1) Automated Machine Learning (what it is? + 1 potential application example in ITS?)(2) Deep Autoencoder (what it is? + 1 in potential application example in ITS?)(3) Denoising Autoencoder (what it is? + 1 potential application example in ITS?)(4) LSTM (what it is? + 1 potential application example in ITS?)(5) Generative Adversarial Networks (what it is? + 1 potential application example in ITS?)(6) Spiking Neural Networks (what it is? + 1 potential application example in ITS?)(7) Restricted Bolzmann Machines (what it is? + 1 potential application example in ITS?)(8) Deep-Belief Neural Networks (what it is? + 1 potential application example in ITS?)(9) Reinforcement Learning (what it is? + 1 potential application example in ITS?)(10) Graph Analytics and Deep Learning (what it is? + 1 potential application example in ITS?)(11) Convolution Neural Networks (what it is? + 1 potential application example in ITS?)

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The grading will be based on the project results,  presentations and an exposé at the end of the course

topics are related to the project

the standards of assessment for examinations are given by fulfilling requirements of the written exam