Python Machine Learning (I Mean Python Computer Vision…)

I found a squirrel while chasing another squirrel.  The original squirrel was Python Computer Vision.  The distracting squirrel ended up being Python Machine Learning.  Here are some not-to-be-forgotten URLs that came up (some, even further squirrels themselves!) –

The website to accompany the book “OpenCV with Python Blueprints” – https://github.com/mbeyeler/opencv-python-blueprints

Kaggle “Titanic: Machine Learning from Disaster” competition site (Data Science site, in Python, R, …) – https://www.kaggle.com/c/titanic#tutorials

XGBoost: Improving the output of machine learning by combining multiple algorithms (quick, efficient, scalable) – https://arxiv.org/abs/1603.02754 and https://github.com/dmlc/xgboost

Machine Learning – Ensembling/Stacking in Python – https://www.kaggle.com/arthurtok/introduction-to-ensembling-stacking-in-python

Machine Learned – “I do not think that word means what you think it means” – https://github.com/benhamner/cleverhans and the talk that inspired it – http://ieeexplore.ieee.org/document/6847693/?reload=true

ML Learning Evaluation Metrics – https://github.com/benhamner/Metrics

Simple-to-use Tutorials for TensorFlow (at least, that’s the claim…) – https://github.com/astorfi/TensorFlow-World

Python 2.7 Aerial/Satellite Imagery Feature Identification – https://github.com/azavea/raster-vision

Google Word2Vec – a pre-trained model! – http://mccormickml.com/2016/04/12/googles-pretrained-word2vec-model-in-python, the Kaggle version – https://www.kaggle.com/c/word2vec-nlp-tutorial, code – https://github.com/danielfrg/word2vec and a Jupyter notebook – http://nbviewer.jupyter.org/github/danielfrg/word2vec/blob/master/examples/word2vec.ipynb

(Whew!)

Check today’s other posts for squirrels found while this squirrel chased away the other squirrel….

– Squirrel01