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Build & Deploy SciKit Learn Machine Learning Model with AWS Sagemaker

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Build & Deploy SciKit Learn Machine Learning Model with AWS Sagemaker and Integrate it to Lambda, API Gatway

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning. In this tech talk, we will introduce you to the concepts of Amazon SageMaker including a one-click training environment, highly-optimized machine learning algorithms with built-in model tuning, and deployment of ML models. With zero setup required, Amazon SageMaker significantly decreases your training time and the overall cost of getting ML models from concept to production.

AWS Lambda lets you run code without provisioning or managing servers. You pay only for the compute time you consume.

Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale. APIs act as the "front door" for applications to access data, business logic, or functionality from your backend services.

Check out this tutorial for this code : https://youtu.be/2-mCo7q2Iw4

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Build & Deploy SciKit Learn Machine Learning Model with AWS Sagemaker

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  • Jupyter Notebook 54.4%
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