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Showing posts from May, 2017

Jaccard Similarity vs Cosine Similarity

https://datascience.stackexchange.com/questions/5121/applications-and-differences-for-jaccard-similarity-and-cosine-similarity Jaccard Similarity is given by sij=pp+q+rsij=pp+

The Black Magic of Deep Learning - Tips and Tricks for the practitioner

via: https://nmarkou.blogspot.co.uk/2017/02/the-black-magic-of-deep-learning-tips.html

I've been using Deep Learning and Deep Belief Networks since 2013.
I was involved in a green field project and I was in charge of deciding the core Machine Learning algorithms to be used in a computer vision platform.

Nothing worked good enough and if it did it wouldn't generalize, required fiddling all the time and when introduced to similar datasets it wouldn't converge. I was lost. I then caught wind from Academia, the new hype of Deep Learning was here and it would solve everything.

I was skeptical, so I read the papers, the books and the notes. I then went and put to work everything I learned.  Suprisingly, it was no hype, Deep Learning works and it works well. However it is such a new concept (even though the foundations were laid in the 70's) that a lot of anecdotal tricks and tips started coming out on how to make the most of it (Alex Krizhevsky covered a lot of them and in so…