ogrisel's notebook

This is a bunch of IPython notebooks documents with mostly unfinished ML related experiments.

Some of them can be executed in a basic numpy / scipy / pandas / matplotlib / scikit-learn environment for instance using:

Name		Name	Last commit message	Last commit date
Attention		Attention
Overfitting		Overfitting
Reinforcement Learning		Reinforcement Learning
dask		dask
fmri_vae		fmri_vae
generalization		generalization
gmm		gmm
gradients		gradients
letor_cluster		letor_cluster
representations		representations
screenshots		screenshots
sklearn_demos		sklearn_demos
.gitignore		.gitignore
Adjusted Variable Importances with Randomized Trees.ipynb		Adjusted Variable Importances with Randomized Trees.ipynb
Bootstrap.ipynb		Bootstrap.ipynb
Clustering Model Selection.ipynb		Clustering Model Selection.ipynb
Data Preprocessing for the Learning to Rank example.ipynb		Data Preprocessing for the Learning to Rank example.ipynb
Distributed Aggregate and Join.ipynb		Distributed Aggregate and Join.ipynb
Distributed Learning of Extra Trees with IPython.parallel.ipynb		Distributed Learning of Extra Trees with IPython.parallel.ipynb
Explained variances.ipynb		Explained variances.ipynb
Function Approximation.ipynb		Function Approximation.ipynb
GP overfitting.ipynb		GP overfitting.ipynb
Gradient.ipynb		Gradient.ipynb
Labeled Faces in the Wild recognition.ipynb		Labeled Faces in the Wild recognition.ipynb
Learning to Rank.ipynb		Learning to Rank.ipynb
MNIST8M Chunking and Upload to Cloud Blob Storage.ipynb		MNIST8M Chunking and Upload to Cloud Blob Storage.ipynb
Non IID cross-validation.ipynb		Non IID cross-validation.ipynb
Numa-aware computation experiments.ipynb		Numa-aware computation experiments.ipynb
Numba Parakeet Cython.ipynb		Numba Parakeet Cython.ipynb
Numpy intro.ipynb		Numpy intro.ipynb
Parameter search for Extra Trees on the MNIST classificationt task.ipynb		Parameter search for Extra Trees on the MNIST classificationt task.ipynb
Patch-Based Feature Extraction for Image Classification.ipynb		Patch-Based Feature Extraction for Image Classification.ipynb
README.md		README.md
SGD stuff.ipynb		SGD stuff.ipynb
Saddle Point LBFGS.ipynb		Saddle Point LBFGS.ipynb
Semi-supervised Extra Trees.ipynb		Semi-supervised Extra Trees.ipynb
Text Classification.ipynb		Text Classification.ipynb
Time Series.ipynb		Time Series.ipynb
Untitled Diagram.drawio		Untitled Diagram.drawio
Variable Importance with Completely Randomized Trees.ipynb		Variable Importance with Completely Randomized Trees.ipynb
bench_gb_libraries.ipynb		bench_gb_libraries.ipynb
bench_script.py		bench_script.py
cloudstorage.ini.example		cloudstorage.ini.example
environment.yml		environment.yml
epistemic_estimation_for_classification.ipynb		epistemic_estimation_for_classification.ipynb
heteroscedastic_optimization_via_surrogate_modeling.ipynb		heteroscedastic_optimization_via_surrogate_modeling.ipynb
nmf_topics.ipynb		nmf_topics.ipynb
poly_reg_array_api.ipynb		poly_reg_array_api.ipynb
poly_reg_array_api_vs_tabicl.ipynb		poly_reg_array_api_vs_tabicl.ipynb
probabilistic_regression_figures.ipynb		probabilistic_regression_figures.ipynb
quantile_regression_as_classification.ipynb		quantile_regression_as_classification.ipynb
ridgeclassifier_and_calibration_pytorch.ipynb		ridgeclassifier_and_calibration_pytorch.ipynb
structure_digits.ipynb		structure_digits.ipynb
test.drawio		test.drawio
ubuntu-quickstart.sh		ubuntu-quickstart.sh

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