[{"data":1,"prerenderedAt":40},["ShallowReactive",2],{"repo-aws-serverless-cicd-workshop":3},{"id":4,"title":5,"contributors":6,"date":8,"description":9,"diagram":10,"extension":11,"framework":12,"gitHub":13,"introBox":16,"language":19,"meta":21,"resources":22,"services":28,"simplicity":35,"stem":36,"type":37,"usecase":38,"__hash__":39},"repos\u002Frepos\u002Faws-serverless-cicd-workshop.json","Serverless Inference Workshop",[7],"content\u002Fcontributors\u002Fjulian-wood.json","2023-02-08","Use AWS Machine Learning services to train a model and make inferences against the model using AWS Lambda so costs are appropriately controlled.","\u002Fassets\u002Fimages\u002Frepos\u002Faws-serverless-cicd-workshop.jpg","json",[],{"template":14},{"repoURL":15},"https:\u002F\u002Fgithub.com\u002Faws-samples\u002Faws-serverless-cicd-workshop",{"headline":5,"text":17},[9,18],"Create a serverless data processing pipeline using AWS Lambda, Amazon S3, and Amazon SQS. You will then use AWS Machine Learning services to train a model. Finally you will make inferences against the model using AWS Lambda so our costs are appropriately controlled.",[20],"Python",{},{"headline":23,"bullets":24},"Additional resources",[25],{"text":26,"link":27},"Workshop instructions","https:\u002F\u002Fgithub.com\u002Faws-samples\u002Faws-serverless-workshops\u002Ftree\u002Fmaster\u002FMachineLearning",[29,30,31,32,33,34],"lambda-event-functions","s3","sqs","athena","glue","apigw","300","repos\u002Faws-serverless-cicd-workshop","Workshop","AI\u002FML\u002FGenAI","Kc1_eS6u5qsq0t7Z6fRdE8u3Wp4VTtxjIx3bEUA8-8k",1792665263488]