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Name	Last commit	Last update
images/neuralnets
.gitignore
01_introduction.ipynb
02_classification.ipynb
03_overfitting_and_cross_validation.ipynb
04_measuring_quality_of_a_classifier.ipynb
05_classifiers_overview.ipynb
06_preprocessing_pipelines_and_hyperparameter_optimization.ipynb
07_regression.ipynb
2d_points.csv
LICENSE
Notes Review 01 and 02.ipynb
README.md
accuracy_training_vs_eval.svg
beers.csv
beers_eval.csv
circle.csv
classification-svc-2d-poly.png
classifier_examples.ipynb
cluster-image.png
concepts.md
course_layout.md
create_datasets.py.ipynb
cross_eval_and_test.svg
cross_val_0.png
cross_val_0.svg
cross_val_1.png
cross_val_1.svg
cross_val_2.png
cross_val_2.svg
cross_val_3.png
cross_val_3.svg
custom.html
data_split.png
decision_boundaries.ipynb
graphics.ipynb
index.ipynb
line_separable_2d.csv
machine_learning_workshop_proposal.ipynb
mlw_packages.yml
neural_nets_intro.ipynb
nonlin-pca.png
precision_high_recall_low.svg
precision_low_recall_high.svg
regression-lin-1d.png
requirements_dev.txt
salmon.csv
scikit-learn_ml_map-classification.png
stochastic-vs-batch-gradient-descent.png
svm_margin.png
xor.csv

README

Material related to planned machine learning workshop.