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Materials + ML Workshop
Introduction
Installing Python and Jupyter Notebook
Using Google Colab
Getting Started with Python
Python Basics
Logic and Flow Control
Loops
Python Data Types
Sets and Dictionaries
Python Functions and Classes
Classes and Object-Oriented Programming
Scientific Computing with Numpy and Scipy
The Numpy Package
The Scipy Package
Data Handling and Visualization
Data Visualization with Matplotlib
Materials Science Python Packages
ASE - The Atomic Simulation Environment
Pymatgen and the Materials Project API
Introduction to Machine Learning
Statistics Review
Mathematics Review
Supervised Learning
Fitting Supervised Models
Application: Classifying Perovskites
Advanced Regression Models
Kernel Machines
Application: Bandgap Prediction
Unsupervised Learning
Feature Selection and Dimensionality Reduction
Clustering and Distribution Estimation
Application: Classifying Superconductors
Neural Networks
Basic Neural Networks
Training Neural Networks
Neural Network Architectures
Applications of ML to Materials Science
ALIGNN Tutorial
Repository
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