study days on deep learning and big data challanges

Abstract

hese study days are part of the activities of the LMSA laboratory (Laboratoire des Mathématiques et Sciences Appliquées) and within the framework of the training to strengthen the doctoral program in computer science "Artificial Intelligence and Big Data" for the year 2021/2022." Deep learning, a subfield of machine learning, uses artificial neural networks with multiple layers to learn from data. With the rise of big data comes the need for scalable and efficient deep learning algorithms that can handle massive amounts of data while still maintaining accuracy and interpretability of the outputs. In this context our study days try to highlight the challenges associated with deep learning and big data from the perspective of computer science. The program of the study days aims to be progressive, from initiation to an advanced stage of the topic being addressed. It includes an historical overview of artificial intelligence, a simple introduction to machine learning, a discussion of big data challenges, and some advanced technologies of deep learning as fine tuning LLM, generative models, deep reinforcement learning, and advanced deep learning models