How Can I Specify Content_type In A Training Job Of Xgboost From Sagemaker In Python?

I am trying to train a model using the sagemaker library. So far, my code is the following: container = get_image_uri(boto3.Session().region_name, 'xgboost',

Solution 1:

I have solved it using s3_input objects:

s3_input_train = sagemaker.s3_input(s3_data='s3://antifraud/production/data/{domain}-{product}-{today}/train_data.csv',
content_type='text/csv')
s3_input_validation = sagemaker.s3_input(s3_data='s3://antifraud/production/data/{domain}-{product}-{today}/validation_data.csv',
content_type='text/csv')

train_config = training_config(estimator=estimator,
inputs = {'train':s3_input_train,
          'validation':s3_input_validation})