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git.ir
Mastering MLOps: Complete course for ML Operations
Advanced hands-on bootcamp of MLOps with MLFlow, Scikit-learn, CI/CD, Azure, FastAPI, Gradio, SHAP, Docker, DVC, Flask..
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Aug 30, 2023
MLOps Best Practices
MLOps Checklist β 10 Best Practices for a Successful Model Deployment
neptune.ai
Jul 21, 2022
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18 reactions · 22 shares | MLOps is a set of practices and tools for streamlining the deployment, maintenance, and management of ML models in a production environment. The goal of MLOps is to ensure that models are reliable, secure, and scalable, while also making it easier for data scientists and engineers to develop, test, and deploy ML models. Read more: https://hubs.la/Q02fGY810 #mlops #machinelearningops | Data Science Dojo | Facebook
Facebook
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296 views
3 weeks ago
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Understand the full ML engineering lifecycleβfrom model building to deployment using MLOps best practices. | SCALER | Facebook
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