Algorithm-Agnostic Model Building with MLflow

Author:Murphy  |  View: 22098  |  Time: 2025-03-23 11:54:05

One common challenge in MLOps is the hassle of migrating between various algorithms or frameworks. This beginner-friendly article helps you tackle the challenge by leveraging algorithm-agnostic model building using mlflow.pyfunc.

Why Agorithm-Agonostic Model Building?

Consider this scenario: we have an sklearn model currently deployed in production for a particular use case. Later on, we find that a deep learning model performs even better. If the sklearn model was deployed in its native format, transitioning to the deep learning model could be a hassle

Tags: Databricks Datascience Training Machine Learning Mlflow Mlops

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