Research projects in Machine Learning
conda create -n ml-research
source activate ml-research
make deps
Install OpenML
git clone https://github.com/openml/openml-python
cd openml-python
python setup.py install
cd ..
rm -rf openml-python
Install jupyter lab extensions:
jupyter labextension install @jupyterlab/plotly-extension
The gan_gaussian project is a basic intuition-builder for GANs. It implements
as simple GAN that tries to learn a gaussian (normal) distribution. The project
results can be reproduced by running:
cd gan_gaussian
python basic_gan.py
Running the script produces a few artifacts that are meant to help build some intuition about how GANs work and what kinds of distributions it learns when the generator is trying to trick the discriminator into accepting the generator's fake samples.
gan_gaussian_plot.pnggan_gaussian_evolution.png
MetaRL-based Estimator using Task-encodings for Automated machine Learning
META Learn is a deep learning approach to automated machine learning that parameterizes the API of machine learning software as a sequence of actions to select the hyperparameters of a machine learning pipeline in an end-to-end fashion, from raw data representation, imputation, normalizing, feature representation, and classification/regression. Currently the [sklearn API][sklearn] is the only supported ML framework.