geocomp-ml-short.yaml

# 2-half-days shallow learning intro class for geos.
title: Intro to Machine Learning for Subsurface
environment: geoml
conda:
  - umap-learn
  - hdbscan
  - verde
curriculum:
  1a:
    - Quick course overview
    - Introductions
    - A quick introduction to supervised classification  # Conceptual only.
    - Multiclass_classification_1_Split_and_scale.ipynb
  1b:
    - Multiclass_classification_1_Split_and_scale.ipynb  # Continued
    - Check out and feedback
  2a:
    - Check in and review
    - Multiclass_classification_2_Fit_and_score.ipynb
  2b:
    - Multiclass_classification_3_Tune_and_save.ipynb
    - Check out and feedback
extras:
  - Binary_classification.ipynb
  - Image_classification.ipynb
  - Latent_semantic_analysis.ipynb
  - Making_maps_with_machine_learning.ipynb
  - Pandas_for_timeseries.ipynb
  - Quick_intro_to_Dask.ipynb
  - Read_and_write_LAS.ipynb
  - Read_SEG-Y_with_segyio.ipynb
  - Regression_with_Scikit-Learn.ipynb
  - Unsupervised_clustering_on_rock_properties.ipynb
  - What_is_gradient_descent.ipynb
scripts:
  - mlutils.py  # Copied to all notebook directories.
references:
  - Dramsch_2020.pdf
  - Karpatne_etal_2017.pdf
  - ML_project_review_checklist.pdf
  - Raschka_2018.pdf