🔬 ML4MS: Machine Learning for Materials Science

A knowledge initiative documenting Applied AI techniques for Materials Science and Engineering

🎯 Mission

ML4MS bridges the gap between materials engineering and modern machine learning. This platform provides practical tutorials, case studies, and best practices for applying ML to materials problems.

📚 What You'll Find

• Tutorials: Step-by-step guides for ML in materials science
• Case Studies: Real-world applications of ML to materials problems
• Best Practices: Guidelines for feature engineering, model selection, and validation in materials informatics
• Resources: Curated list of datasets, papers, and tools

🚀 Featured Content

• Beyond FEA: Solving the ‘Small Data’ Problem with Physics-Informed AI
• 800 Years in Weeks: Decoding Google DeepMind’s GNoME
• From Atoms to Algorithms: How AI ‘Sees’ Materials

👨‍🔬 About

Created by Ahmed Aburakhia, a Machine Learning Engineer with expertise in materials science and 12 years of industrial experience.

📬 Connect

• LinkedIn: linkedin.com/in/ahmedaburakhia
• Email: aaburak@uwo.ca

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