Ai4MatLectures
PyTorch teaching notebooks for materials science
Teaching notebooks for the ECLIPSE Lab lecture triad at FAU Erlangen-Nürnberg. Install the package:
pip install git+https://github.com/ECLIPSE-Lab/Ai4MatLectures.git "mdsdata>=0.1.5"MFML — Mathematical Foundations of AI & ML
| Week | Topic | Dataset | Notebook |
|---|---|---|---|
| 3 | Regression from scratch | Tensile Test | week03_regression_tensile |
| 4 | First nn.Module classifier | Iris | week04_classifier_iris |
| 5 | Manual backprop | Alpaydin Digits | week05_backprop_digits |
| 7 | Overfitting & regularization | Ising light | week07_overfitting_ising_light |
| 10 | Autoencoder latent space | Ising full | week10_autoencoder_ising_full |
| 11 | Unsupervised clustering | Nanoindentation | week11_clustering_nanoindentation |
MLPC — ML in Materials Processing & Characterization
| Week | Topic | Dataset | Notebook |
|---|---|---|---|
| 4 | Baseline before CNNs | Alpaydin Digits | week04_baseline_digits |
| 5 | First CNN | Ising light | week05_cnn_ising_light |
| 5 | Full CNN training | Ising full | week05_cnn_ising_full |
| 7 | Process monitoring | Tensile Test | week07_process_monitoring_tensile |
| 11 | Anomaly detection via AE | Cahn-Hilliard | week11_anomaly_cahn_hilliard |
MG — Materials Genomics
| Week | Topic | Dataset | Notebook |
|---|---|---|---|
| 5 | Descriptors + regression | Chemical Elements | week05_descriptors_elements |
| 8 | Regression & generalization | Nanoindentation | week08_regression_nanoindentation |
| 11 | Latent space (Ising) | Ising light | week11_latent_ising |
| 11 | Materials latent space | Cahn-Hilliard | week11_latent_cahn_hilliard |