├── .gitignore ├── Data Sets └── milling_uc_berkeley │ ├── processed │ ├── data_processed.zip │ ├── labels_with_tool_class.csv │ └── models │ │ └── best_models │ │ ├── 20200620-053315_bvae │ │ ├── model.json │ │ └── weights.h5 │ │ ├── 20200620-053315_encoder │ │ ├── model.json │ │ └── weights.h5 │ │ └── best_models.zip │ └── raw │ └── mill.zip ├── Feature Engineering ├── sample_signal.csv └── svd.ipynb ├── LICENSE ├── Metal Machining ├── 1.A_milling-data-exploration.ipynb ├── 1.B_building-vae.ipynb ├── 1.C_anomaly-results.ipynb ├── data_prep.py ├── images │ ├── case_11_trend.svg │ ├── case_13_trend.svg │ ├── cut_signals.png │ ├── face_milling.svg │ ├── flank_wear.svg │ ├── latent_space_cnc.png │ ├── model_architecture.svg │ ├── prauc_cnc.svg │ ├── prauc_params.svg │ ├── prauc_params_cnc.svg │ ├── prauc_results.svg │ ├── simple_trend.png │ ├── thresholds.png │ ├── trend_spash_image.png │ ├── vae.png │ ├── vae.svg │ ├── vae_training_random_search.png │ ├── vae_training_step3.jpg │ └── 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