Recommended by a colleague.
We can store trained models in a binary file for later use.
joblib works especially well with NumPy arrays which are used by sklearn so depending on the classifier type you use you might have performance and size benefits using joblib.
Otherwise pickle does work correctly so saving a trained classifier and loading it again will produce the same results no matter which of the serialization libraries you use. See also the docs of sklearn on this topic.
Please note that joblib is included in sklearn.
Test the following for your model
1. Final binary file size
2. Total foot memory footprint
3. Time to load
AI is having the following categories:
Natural language processing
Automated speech recognition
Examples on: 8 Queen problem, Magic Squares,…etc