Sets up a VM with the essential Python (pandas, scikit-learn, xgboost) & R packages helpful for Kaggle competitions
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README.md
Vagrantfile
jupyter_application_config.py
provision.sh
requirements.txt

README.md

Kaggle Virtual Machine

Sets up a VirtualBox VM with the essential Python (pandas, scikit-learn, xgboost, Keras) and R packages installed. A Vagrant file is used to set up this VM, which runs on Ubuntu 14.04.

Getting Started

I assume you already have VirtualBox (version 5+) installed, if you don't, please download and install it.

  1. Download and install Vagrant if you haven't previously done so.
  2. Create 2 sibling folders kaggle and kaggle-vm
  3. Change into the kaggle-vm folder and run vagrant up -- this creates the VM. The Vagrantfile maps the kaggle folder as a synced_folder within the VM.

What's Installed

  • Python, 3.5.2
    • numpy, 1.11.1
    • pandas, 0.18.1
    • prophet, 0.1.1
    • scikit-learn, 0.18.1
    • scipy, 0.18.1
    • xgboost, 0.6a2
    • Some other packages, refer to requirements.txt
  • R version 3.3.2
    • R packages data.table, dplyr, glmnet, randomForest, xgboost and 90+ other packages (refer to the R Essentials bundle)
  • Deep Learning,
    • Keras, 2.0.5
    • TensorFlow, 1.3.0
    • Theano, 0.8.2

In addition, a Jupyter notebook server is also installed. You can view it from the host's browser at http://localhost:9000. Password is password.