SEMIT Organization Sympatizes with all people affected by the recent earthquake in these sorrowful days.
Considering the disaster, Machine Learning workshop will be postponed to March 13-14, 2023.
Machine Learning: Select and Implement
Machine learning is the science of programming machines to perform human tasks without being explicitly programmed. Email spam recognition, spelling checkers and platforms video recommenders are commonly encountered machine learning applications that we are exploring in our everyday life. In this workshop, two learning objectives are targeted. First, acquiring practical implementation of machine learning algorithms using Python. Second, the key criteria to help to select adequate machine learning algorithm given a particular case study.
For the purpose of the first objective, a comprehensive review of algorithms covering major machine learning models is provided. Afterwards, specified labs are animated using python. We propose the Simple Linear regression, the Multiple Linear regression and the Logistic regression to deal with the regression models. The Decision Tree, the Random Forest and the Naïve Bayes for classification models; and the K-means, the Nearest Neighbors (NN) and the Support Vector Machine (SVM) for the clustering ones.
To accomplish the second objective, we will introduce some popular use cases of Machine Learning and go through Machine Learning interview questions to assess practical market expectations.
Lecturers
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Prof. Safa Bhar Layeb LR-OASIS, National Engineering School of Tunis, University of Tunis El Manar, Tunis, Tunisia |
Dr. Marwa Hasni LR-OASIS, National Engineering School of Tunis, University of Tunis El Manar, Tunisia |
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Lecturers Short Bio
Safa Bhar Layeb is a professor of industrial engineering and a member of the OASIS Lab at the National Engineering School of Tunis, Tunisia. She is Polytechnic Engineer and has obtained her Master’s in Mathematical Engineering, PhD in Applied Mathematics, and HDR in Industrial Engineering. She is the founding chair of the African Working Group in Health Systems, affiliated with the African Federation of Operational Research Societies (AFROS). She is particularly interested in data science and industrial engineering approaches and their applications in network design, logistics and healthcare.
Marwa Hasni is Assistant professor in Industrial Engineering at ISSIG Gabes – University of Gabes. She holds a PhD in Industrial Engineering from Ecole Nationale d'Ingénieurs deTunis - University of Tunis El Manar and member of the Laboratory of Economics and Applied Finance (LEFA) since 2021. She also holds a diploma of Engineer in Industrial Engineering and Logistics of the National Engineering School of Carthage-University of Carthage. Her research focuses on the development and the analysis of forecasting techniques applied to production systems and to financial and banking systems. The interest being non-parametric sampling techniques and those associated with the Machine learning and deep learning approaches. Marwa Hasni has published and reviewed a number of research studies on the side of several international journals namely: International Journal of Production Economics, International Journal of Production Research, International Journal of Decision Sciences, Risk and Management, Managerial and Decision Economics, International Journal of Economics, and Strategic Management of Business Processes.
Workshop sessions and links
Machine Learning workshop will be held in 4 sessions as below detailed:
All SEMIT programs are scheduled based on Ankara time zone (GMT +3)
Session 1: (13.03.2023, 9-12) https://us02web.zoom.us/j/84385292574
Session 2: (13.03.2023, 14-17) https://us02web.zoom.us/j/83716718958
Session 3: (14.03.2023, 9-12) https://us02web.zoom.us/j/84801411994
Session 4: (14.03.2023, 14-17) https://us02web.zoom.us/j/83158579948
Workshop time table
