Head First Python by Paul Barry Buy on Amazon Chapter 4. Persistence: Saving data to filesIt is truly great to be able to process your file-based data. But what happens to your data when you’re done? Of course, it’s best to save your data to a disk file, which allows you to...
> etc for a python application and I am looking for a package that does this > in a way that is portable across unix/linux and windows (and mac would be > nice as well).[/color] Thank you all for the replies. I have a few options to try now. I'm using wxPython so might inve...
There are two routes for developing and deploying the machine learning model: 1. Training the model and get a persisted model; 2. Apply the model to production batch or streaming input. Typically, these two processes might share the same configuration files for data cleaning, transformation etc....
Using PickleRegistryMixin Add the mixin to a Python class for seamless registry integration: from litmodels.integrations.mixins import PickleRegistryMixin class MyModel(PickleRegistryMixin): def __init__(self, param1, param2): self.param1 = param1 self.param2 = param2 # Your model initializat...
fit(X_train, y_train) # Upload the saved model using litmodels upload_model(model=model, name=MY_MODEL_NAME) Download and Load the Model for inference from litmodels import load_model # Unique model identifier: <organization>/<teamspace>/<model-name> MY_MODEL_NAME = "your_org/your_team...