Applied Mathematics Notebooks Repository:Collection of Google Colab Notebooks (github.com)

The Applied Mathematics Notebooks repository has been launched, offering a rich collection of Google Colab notebooks that delve into various applied mathematics topics. Covering areas such as numerical simulations, machine learning, and optimization techniques, these resources provide practical, hands-on implementations suitable for both students and professionals in the AI/ML community. Users can easily access the notebooks through the provided GitHub link and run them sequentially to explore core concepts in real-world applications. This repository is significant as it bridges theoretical mathematics with applicable technologies, supporting the exploration of complex topics like fluid dynamics via Smoothed Particle Hydrodynamics, and machine learning applications like adversarial search and control optimization. Each notebook operates on Python 3.10.12 and has specific requirements outlined for ease of use, showcasing a range of methodologies from Monte Carlo simulations to deep reinforcement learning for controlling systems. The collection not only aids in educational pursuits but also encourages the practical application of mathematical principles in AI and machine learning frameworks, fostering further innovation in these fields.