Deploying machine learning models as serverless APIs Amazon Web Services

Machine learning (ML) practitioners gather data, design algorithms, run experiments, and evaluate the results. After you create an ML model, you face another problem: serving predictions at scale cost-effectively. Serverless technology empowers you to serve your model predictions without worrying about how to manage the underlying infrastructure. Services like AWS Lambda only charge for the amount of time that you run your code, which allows for significant cost savings. Depending on latency and memory requirements, AWS Lambda can be an excellent choice for easily deploying ML models.