You can export your model using joblib.
Now, something I like to use for easy deployment is pipedream. So you can upload the file generated from joblib anywhere, call it using pipedream and then you can use webhooks to trigger the workflow.
Also there is other many options, heroku, pythonanywhere, Azure, GC, AWS, where you can store this file and make it run with new data.
There are libraries where you can deploy easier like gradio or plotly if you are in a hurry.
Orient, please, on a following question.
I created an ML model in Jupiter notebook (python) based on the internal data of the company where I work. The management suggests "wrapping" this model, making something like a finished boxed product for use outside the company.
Can you tell me how this can be technically implemented?
And is it possible to make a ready-made boxed product out of Jupiter at all?
I have no ideas besides sharing the file on GitHub.
ML model as a boxed solution for sale outside