Suhas Adiga - Useful Resource

Python for Materials Science

A GitHub repository containing tutorials on Python utilities relevant to Materials Science, covering topics from basic concepts to advanced libraries in the field. The content is presented in the way I have learned and applied it throughout my work. The repository is expected to be completed within 10 weeks. Feedback and suggestions for improvement are welcome.

Link to GitHub Repository.

Machine Learning

Basic Machine Learning

[1] Stanford CS 229 : Machine Learning, taught by Prof. Andrew NG

[2] University of Waterloo SYDE522 : Machine Intelligence (Winter 2019), taught by Professor H.R. Tizhoosh

Machine Learning relevant to Materials Science

[1] Imperial College London MATE70026 : Machine Learning For Materials, taught by Prof. Aron Walsh

[2] F. Oviedo, K. T. Butler, and P. Canepa, Machine Learning in Materials Science (Wiley-VCH, 2024)

[3] Introduction to Materials Informatics : By Prof. Enze Chen and Prof. Mark Asta

[4] Materials Informatics, by Prof. Taylor Sparks (available on YouTube)

Scientific Slide Design

[1] Make Attractive Scientific Figures in PowerPoint – Tutorial on color, fonts, and positioning by Dr. Anubhav Jain, available on the Atom to Materials YouTube channel.

[2] Ram Seshadri’s Slides – Guidance on preparing clear figures and graphics for presentations and publications*.

[3] Coolors – A powerful tool for generating color palettes and gradients for clean, visually appealing slides*.

[4] WebAIM: Color Contrast Checker – Tool for ensuring text and background colors meet accessibility standards*.

*Introduced to me by my senior, Dr. Arijit Sinha, grateful for his guidance.

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