python regression for big data by vowpalwabbit

1 ridge
2 lasso
3 quantile for both ridge and lasso !

VowpalWabbit
https://github.com/VowpalWabbit/vowpal_wabbit/wiki/Command-Line-Arguments

for big data like
us-used-cars-dataset 9 GB 3ml rows 66 features predict price
https://www.kaggle.com/ananaymital/us-used-cars-dataset

all calculations done in vowpalwabbit python including one hot for categorical data (not scikit learn or pandas one hot)

data has both categorical and continues features



code starter
https://github.com/matanbruker/mechine-learning-project/blob/1583c3790fe9d09608e8805e573b6493bc7bcbc1/mechine%20learning%20project/Notebooks/analcatdata_neavote.ipynb

2
Feature-interactions 2nd and 3d order for categorical data
https://github.com/VowpalWabbit/vowpal_wabbit/wiki/https://github.com/VowpalWabbit/vowpal_wabbit/wiki/Feature-interactions
3
hyper parameters tuning
https://github.com/VowpalWabbit/vowpal_wabbit/wiki/Using-vw-hypersearch
4
train test split