fastai / Randomized Svd
demos for PyBay talk: Using Randomness to make code faster
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This is the demo for my PyBay 2017 talk. If you are not comfortable setting up the demo or unable to do so, you will still get a lot out of the session.
I recommend downloading Anaconda, which contains the main Python scientific libraries. Alternately, you can create a virtual environment and install the necessary requirements:
virtualenv env
source env/bin/activate
pip install -r requirements.txt
To start the jupyter notebook from the command line:
jupyter notebook
Data Sources
Part 1: Word Embeddings
The dataset of word embeddings is available at http://files.fast.ai/models/glove/6B.100d.tgz To download and unzip the files from the command line, you can run:
wget http://files.fast.ai/models/glove_50_glove_100.tgz
tar xvzf glove_50_glove_100.tgz
Part 2: Background Removal
Download the real video 003 and 008 datasets from BMC 2012 Background Models Challenge Dataset
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