🔬 EMLOV4 dives deep into the world of MLOps, exploring advanced techniques and tools crucial for success in production environments. From Docker and PyTorch Lightning to AWS and Kubernetes, this course equips you with the knowledge and skills needed to excel in the rapidly evolving field of machine learning operations.
Contains solutions for assignments and learning from Extensive Machine Learning Operations course of The School of AI https://theschoolof.ai/#programs
Website: [On Development]
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Introduction to MLOps
An overview of MLOps (Machine Learning Operations), covering the best practices and tools to manage, deploy, and maintain machine learning models in production.
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A hands-on session on creating Docker containers from scratch and an introduction to Docker, the containerization platform, and its core concepts.
Learnt about docker fundamentals and how to chose the base docker image and reduce the size as minimal as possible
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An introduction to Docker Compose, a tool for defining and running multi-container Docker applications, with a focus on deploying machine learning applications.
Learnt about docker compose and mounting multiple volumes and handling multiple containers
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An overview of PyTorch Lightning, a PyTorch wrapper for high-performance training and deployment of deep learning models, and a project setup session using PyTorch Lightning.
Learnt about using lighting to train, eval and infer images using a model developed.
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Every month end during course development
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There is a resource file in which i maintain that has concepts and tools which i learnt newly in EMLO-4.0 course.