Accelerate your Machine Learning Workflow

The article compares the time taken to upload a computer vision dataset to Amazon Web Service (AWS) s3 bucket and Hub, with the aim of identifying the fastest method. It uses a large-scale fish segmentation and classification dataset from Kaggle for benchmarking. The results show that using AWS CLI is faster than boto3, but uploading the entire dataset to Hub using parallel computing was 2 times faster than AWS CLI and ~20 times faster than boto3. This indicates that Hub can significantly speed up the data preparation stage in a Machine Learning workflow.