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findtharun/validation.py

Created June 7, 2020 07:35
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validation.py
train_data, validation_data, test_data = np.split(dataset.sample(frac=1, random_state=1729), [int(0.7 * len(dataset)), int(0.9 * len(dataset))])
train_data.to_csv('train.csv', header=False, index=False)
validation_data.to_csv('validation.csv', header=False, index=False)
#UPLOADING AND TRAINING AND VALIDATION TO DATA TO S3 BUCKET
s3_input_train = boto3.Session().resource('s3').Bucket(bucket).Object(os.path.join(prefix, 'train/train.csv')).upload_file('train.csv')
s3_input_validation = boto3.Session().resource('s3').Bucket(bucket).Object(os.path.join(prefix, 'validation/validation.csv')).upload_file('validation.csv')
#MAKING DATA AS LIBSVM or CSV FORMAT
s3_input_train = sagemaker.s3_input(s3_data='s3://{}/{}/train'.format(bucket, prefix), content_type='csv')
s3_input_validation = sagemaker.s3_input(s3_data='s3://{}/{}/validation/'.format(bucket, prefix), content_type='csv')
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