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Resources

Learning resources

A curated set of free tutorials, courses, datasets, and tools for getting started in materials informatics and machine learning.

Materials-Intelligence Tutorials

  • Harvard IACS Seminar 2022
  • Introduction to materials research using machine learning

Self-Learning — Courses & Textbooks

  • Machine Learning by Andrew Ng (Coursera)
  • Data Science by Johns Hopkins University (Coursera)
  • An Introduction to Statistical Learning — Hastie et al.
  • Pattern Recognition and Machine Learning — Bishop
  • Deep Learning — Goodfellow, Bengio, Courville
  • A beginner's guide to using data science for physicists (SlideShare)
  • Citrine Newsletter
  • TensorFlow tutorial documentation
  • Linear Algebra using Python — Dr. Steven L. Richardson

Workshops

  • IPAM, UCLA
  • IACS ComputeFest (Harvard)
  • Citrine Webinars
  • NIST Resource for Materials Informatics (REMI)

Data Availability

  • Kaggle datasets
  • Google Dataset Search
  • Materials Project
  • Citrine datasets platform
  • Materials Cloud
  • NIMS MatNavi
  • AFLOW
  • Computational 2D Materials Database (C2DB)

Data Science Tools

Python Julia R Jupyter / JupyterHub Google Colab Pandas NumPy Matplotlib Plotly Scikit-learn TensorFlow PyTorch Keras GitHub Streamlit
MaterialsIntelligence

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Rensselaer Polytechnic Institute

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