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Part 01 - Introduction to Scikit-learn.ipynb

Part 01 - Introduction to Scikit-learn.ipynb

 
 

Part 02 - Unsupervised Transformers.ipynb

Part 02 - Unsupervised Transformers.ipynb

 
 

Part 03 - Cross-validation.ipynb

Part 03 - Cross-validation.ipynb

 
 

Part 04 - Grid Searches for Hyper Parameters.ipynb

Part 04 - Grid Searches for Hyper Parameters.ipynb

 
 

Part 05 - Preprocessing and Pipelines.ipynb

Part 05 - Preprocessing and Pipelines.ipynb

 
 

Part 06 - Working With Text Data.ipynb

Part 06 - Working With Text Data.ipynb

 
 

Part 07 - Feature Union.ipynb

Part 07 - Feature Union.ipynb

 
 

Part 08 - Out Of Core Learning.ipynb

Part 08 - Out Of Core Learning.ipynb

 
 

Part 09 - Out Of Core Learning for Text.ipynb

Part 09 - Out Of Core Learning for Text.ipynb

 
 

Readme.md

Readme.md

 
 

machine-learning-with-scikit-learn-odscon-SF-2015.odp

machine-learning-with-scikit-learn-odscon-SF-2015.odp

 
 

machine-learning-with-scikit-learn-odscon-SF-2015.pdf

machine-learning-with-scikit-learn-odscon-SF-2015.pdf

 
 

todo.rst

todo.rst

 
 

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Slides and Notebooks for Open Data Science Conference

Materials for the Scikit-learn tutorial at ODSC SF. Please download the materials and install scikit-learn and the jupyter notebook to follow along. Please use Jupyter / IPython in Version 4.0 or higher. The tutorial requires scikit-learn 0.15 or higher (current is 0.17).

Please check back for changes to the material. It is recommended to update right before the tutorial.

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Material for ODSCON San Francisco 2015

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