Initial commit - training a SGD regressor
Implemented model testing and scoring
Removed Yelp data files
Ignoring Yelp data folder for now
Ignoring derived data folder for now
Trying out polynomial regression on review text length; fixed a plotting bug
Plugged in RMSLE scoring
Implemented prediction on Yelp's test data
Added user review count feature
Ignore patterns
Set training to work only on the training set
Set gradient descent iterations to 1000
First step towards a new pipeline based architecture
Piped based architecture is now on par with previous one
Full switch to pipeline based architecture
Plotting is back
Dropped the SGDR learning rate metaparameters; they were mostly for the unigram feature
Added a sentence count estimator
Added a comment
Created a script for POS vectorizing the reviews