pydata2018_dc_skorch
Pydata DC 2018 (Skorch - A Union of Scikit-learn and PyTorch)
Stars
4
Committers
1
Ecosystems:
Jupyter Notebook
PyData DC 2018
Skorch - A Union of Scikit-learn and PyTorch
Presentation
The slides can be downloaded at: download link.
To clone this repo run:
git clone --depth 1 https://github.com/thomasjpfan/pydata2018_dc_skorch
Setup
To run the notebook locally, please following the following setup procedure:
- Install dependencies:
conda env create -n pydata_dc_2018 -f environment.yml - Activate env:
conda activate pydata_dc_2018
Part 3
- Follow Kaggle's installation and configuration documentation to install and configure the kaggle cli
- Go to Kaggle's 2018 Data Science Bowl Competition, click on "Late Submission" and accept the terms and conditions to get access to the data.
- Run
./dl_extract_prepare.shto download, extract and prepare the data.
Run Jupyter Lab
- Activate env:
conda activate pydata_dc_2018 - Launch jupyter lab:
jupyter lab