mlserve


conda create --name deploy Python=3.8

conda activate deploy

pip install Flask

import pickle
 
# Save the trained model as a pickle string.
filename = 'finalized_model.pkl'
pickle.dump(model, open(filename, 'wb'))

Name		Name	Last commit message	Last commit date
Latest commit History 7 Commits
Procfile		Procfile
README.md		README.md
app.py		app.py
cmd.sh		cmd.sh
finalized_model.sav		finalized_model.sav
requirements.txt		requirements.txt
runtime.txt		runtime.txt

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