July 8, 2019 Development, Machine Learning, Udemy
Deploy Serverless Machine Learning Models to AWS Lambda
Use Serverless Framework for fast deployment of different ML models to scalable and cost-effective AWS Lambda service.
In this course you will discover a very scalable, cost-effective and quick way of deploying various machine learning models to production by using principles of serverless computing. Once when you deploy your trained ML model to the cloud, the service provider (AWS in this course) will take care of managing server infrastructure, automated scaling, monitoring, security updating and logging.
Best Seller Course: A-Z Machine Learning using Azure Machine Learning (AzureML)
What you’ll learn
- Deploy regression, NLP and computer vision machine learning models to scalable AWS Lambda environment
- How to effectively prepare scikit-learn, spaCy and Keras / Tensorflow frameworks for deployment
- How to use basics of AWS and Serverless Framework
- How to monitor usage and secure access to deployed ML models and their APIs
You May Also Need This Course: The Serverless Framework with Node.js & AWS
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