Introduction to Neural Networks for Data Science in Nuclear Physics

Neural networks are a crucial tool in machine learning and the foundation for many modern algorithms, including convolutional neural networks, graph neural networks, and transformers. This tutorial provides a comprehensive introduction to neural networks, specifically tailored for data science applications within nuclear physics. Beginning with fundamental concepts of artificial neurons and network architectures, the session will progress to practical implementations using modern deep learning frameworks. Emphasis will be placed on real-world examples in experimental and theoretical nuclear physics. Attendees will gain a solid understanding of neural network principles and acquire the skills necessary to apply these powerful tools to their research challenges.