Mourad BouneffaIoT Sensor Selection in Cyber-Physical Systems: Leveraging Large Language Models as Recommender SystemsIoT-AID: An Automated Decision Support Framework for IoTA Survey and Perspective View of Meta-Learning for Automated Algorithms Selection and ParametrizationAutomated Machine Learning Hyperparameters Tuning through Meta-Guided Bayesian OptimizationUnlocking the Black Box: Towards Interactive Explainable Automated Machine LearningAMLBID 2.0: An auto-explained Automated Machine Learning tool for Big Industrial DataAMLBID 2.0: An auto-explained Automated Machine Learning tool for Big Industrial DataAutomated Decision Support Framework for IoT: Towards a Cyber Physical Recommendation SystemExplaining Meta-Features Importance in Meta-Learning Through Shapley ValuesAutoencoder-kNN meta-model based data characterization approach for an automated selection of AI algorithmsScalable Meta-Bayesian Based Hyperparameters Optimization for Machine LearningTowards Meta-Learning Based Data Analytics to Better Assist the Domain Experts in Industry 4.0Using meta-learning for automated algorithms selection and configuration: an experimental framework for industrial big dataTowards an automatic assistance framework for the selection and configuration of machine-learning-based data analytics solutions in industry 4.0Towards big industrial data mining through explainable automated machine learningTowards Efficient and Explainable Automated Machine Learning Pipelines DesignAMLBID: An auto-explained Automated Machine Learning tool for Big Industrial DataAMLBID: An auto-explained Automated Machine Learning tool for Big Industrial DataTowards the Automation of Industrial Data Science: A Meta-learning based Approach