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#Precompiler - Unleash the computer on your data Codemash 2017

Amber McKenzie

All attendees should create a kaggle login (https://www.kaggle.com/).

We will be working through the kaggle site so installing the requirements locally is optional. (There are read-only versions of the notebooks if internet troubles crop up)

##Pre-requisite installation (optional)

###Install Python Libraries (automated option): Run command in repo folder: pip install -r requirements.txt

###Install Python Libraries (manual option):

  • numpy
  • jupyter
  • sklearn
  • scipy
  • pandas

##Kaggle dataset links https://www.kaggle.com/c/digit-recognizer

https://www.kaggle.com/c/house-prices-advanced-regression-techniques

https://www.kaggle.com/c/word2vec-nlp-tutorial

https://www.kaggle.com/c/titanic

##Kaggle notebook links https://www.kaggle.com/nlprunner/digit-recognizer/digit-recognizer-with-scikit-learn/

https://www.kaggle.com/nlprunner/house-prices-advanced-regression-techniques/housing-prices-prediction-with-scikit-learn/

https://www.kaggle.com/nlprunner/titanic/titanic-practice-with-scikit-learn/

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