Model Packaging Overview (NLP + MLOps workshop sneak peak)

Channel:
Canada LLMs Explained - Aggregate Intellect - AI.SCIENCE
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Published on ● Video Link: https://www.youtube.com/watch?v=Wpf5EI7uhc0


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Let's Play
Duration: 2:41
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Join our workshop today at https://www.eventbrite.ca/e/premium-hands-on-workshop-build-and-deploy-deep-nlp-models-tickets-94306684833?aff=yt

Machine Learning Operations (ML-Ops) is the process of packaging and deploying ML models into production so that applications can be built on top of those.

This workshop will cover:

Environment setup (AWS, Conda, Github, Docker)
Overview of MLOps (Packaging, Serving, Infrastructure, Operational Considerations)
Cortex.dev demo
Model packaging - High-level overview
Introduction to Pickle, MLflow and ONNX
Docker - High-level overview
Creating Docker images and containers
Introduction to API’s (REST)
Introduction to Flask
Serve a model through Flask
Containerize model / API
Host on EC2 instance
Host on Fargate
Model training pipelines



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Tags:
deep learning
machine learning
mlops
kubernetes
tf serving
sagemaker
pytorch
tensorflow
onnx
model deployment
workshop