Once the model is packaged, it can be deployed to a web server and made available to clients. Models are served as REST APIs and containerized in an isolated environment to serve existing apps or software.
@avikumart_
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ML Models as Web Services: TensorFlow and PyTorch Serving
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1) Web-service In this ML models are served as web services by packaging them in a format that can be consumed by a web service framework, such as TensorFlow Serving or PyTorch Serving.
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Three ML Model Deployment Types for Engineers
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3 Types of ML model deployments to learn about as an ML engineer Web-service
Batch prediction
Streaming -
Model Deployment in Production: MLOps Week 4 Overview
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Week 4 of MLOps Zoom camp ends with the exciting topic of model deployment Let's talk about how models are deployed in prod. under various scenarios
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Master PySpark: Essential Skills for Big Data Engineers
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Pyspark is an essential skill to become a big data engineer Learn Pyspark using the below YT tutorials at FREE of cost
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Data Science ML AI Analytics Resources Follow Guide
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End of this thread! If you are looking to learn more about
Data Science
ML/DL/AI
Analytics
Math & Statistics
Resources
MLOps Then, Don't forget to follow me at @avikumart_ for upcoming posts -
Full Lifecycle ML Model Automation and Real-Time Redeployment
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4) Automated deployment
5) Full lifecycle automation (Including retraining and redeployment of ML models in real-time) Learn more here https://
learn.microsoft.com/en-us/azure/ar
chitecture/example-scenario/mlops/mlops-maturity-model
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MLOps Maturity Model: Five Levels of Production Lifecycle
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2) MLOps maturity model There are 5 levels of the MLOps lifecycle in production 1) No MLOps (Static model deployment, used for POC)
2) DevOps but NO MLOps
3) Automated training (Cont…) -
ML Model Monitoring Performance Degradation Retraining
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– Monitoring Monitoring ML models in production is super important to track performance in real time. If the performance of models degrades it requires retraining and diagnosis to update the quality of ML models in production