Skip to content

Gangadharbhuvan/Traffic_sign_Classification_with_Deep_Learning_using_AWS-Sagemaker

Repository files navigation

Traffic_sign_Classification_with_Deep_Learning_using_AWS-Sagemaker

Classifying Traffic Sign (GTSRB - German Traffic Sign Recognition Benchmark) across 40 different classes with Deep Learning Using AWS (Amazon Web Service) Sagemaker Studio and Deploying in Aws Cloud.

Dataset Link - Here

Predicted Results Here

Steps:

  • Create AWS Account
  • Goto AWS Sagemaker
  • Create a User
  • Goto Sagemaker Studio
  • Create or Upload a Notebook
  • Upload Data, then add to S3 Bucket
  • Use Sagemaker Session, Boto3 to Work with Data, Create Models, Compute and Building Model ...
  • Upload Models (artifacts, Model, Result) to S3 Bucket.
  • Create an Endpoint to Deploy the model Using Sagemaker.
  • [Further integrate Labmbda - API to deploy]
  • Finally Delete the Endpoint to stop charging in AWS Billing.

README Documentation is in progress :)

About

Machine Learning with AWS Sagemaker

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published