Hi ShinyWhale52
This is just a suggestion, but this is what I would do:

1. use clearml-data and create a dataset from the local CSV file
   clearml-data create ... clearml-data sync --folder (where the csv file is)2. Write a python code that takes the csv file from the dataset and creates a new dataset of the preprocessed data
   ` from clearml import Dataset

original_csv_folder = Dataset.get(dataset_id=args.dataset).get_local_copy()

process csv file -> generate a new csv

preprocessed = Dataset.create(...)
preprocessed.add_files(new_created_file)
preprocessed.upload()
preprocessed.close() `3. Train the model (i.e. get the dataset prepared in (2)), add output_uri to upload the model (say to your S3 bucket of clearml-server)

` preprocessed_csv_folder = Dataset.get(dataset_id='preprocessed_dataset_if').get_local_copy()

Train here `

4. Use the clearml model repository (see the Models Tab in the Project experiment table) to get / download the trained model

wdyt?