Sigtuple-Hackathon

These are jupyter notebooks that were used for the Sigtuple AI Challenge hackathon.

Dates of competition: Dec 23rd 2016 to Jan 8th 2017

Achieved a leaderboard rank of 28th without using any deep learning techniques

The hack was interesting, since research for the competition gave me a good overview of image processing techniques

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Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
H2o Implementation v0.ipynb		H2o Implementation v0.ipynb
Image Morphological Snake v1.ipynb		Image Morphological Snake v1.ipynb
Image Morphological Snake v3.ipynb		Image Morphological Snake v3.ipynb
OpenCV - even more CS transforms & histograms v4.ipynb		OpenCV - even more CS transforms & histograms v4.ipynb
OpenCV - more colorspace transformations v3.ipynb		OpenCV - more colorspace transformations v3.ipynb
OpenCV - using Watershed Transformations v1.ipynb		OpenCV - using Watershed Transformations v1.ipynb
OpenCV - using colorspace transformations v2.ipynb		OpenCV - using colorspace transformations v2.ipynb
README.md		README.md
SigTuple Hack - LinearSVC built on pre-processing pipeline v1.1.ipynb		SigTuple Hack - LinearSVC built on pre-processing pipeline v1.1.ipynb
SigTuple Hack - pipeline for preprocessing v1.ipynb		SigTuple Hack - pipeline for preprocessing v1.ipynb
Sklearn - prediction pipeline v2.ipynb		Sklearn - prediction pipeline v2.ipynb
Sklearn - some feature engineering v3.ipynb		Sklearn - some feature engineering v3.ipynb
Using spectral clustering for segmentation.ipynb		Using spectral clustering for segmentation.ipynb
Ward hierarchical clustering & Edge detection.ipynb		Ward hierarchical clustering & Edge detection.ipynb
sklearn - using Sklearn & LinearSVC v1.ipynb		sklearn - using Sklearn & LinearSVC v1.ipynb