Joseph<p>pip install -U mlflow</p><p><a href="https://mastodon.social/tags/MLflow" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MLflow</span></a> 3 has been released.</p><p><a href="https://mastodon.social/tags/ML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ML</span></a> <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a></p>
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InfoQ<p>Explore how to design a <a href="https://techhub.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> pipeline with built-in observability for credit card fraud detection. </p><p>The approach leverages powerful tools like MLflow, Streamlit, Prometheus, Grafana & Evidently AI.</p><p>📖 <a href="https://techhub.social/tags/InfoQ" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>InfoQ</span></a> article: <a href="https://bit.ly/4l0FrBa" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">bit.ly/4l0FrBa</span><span class="invisible"></span></a> </p><p><a href="https://techhub.social/tags/MLflow" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MLflow</span></a> <a href="https://techhub.social/tags/Streamlit" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Streamlit</span></a> <a href="https://techhub.social/tags/Prometheus" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Prometheus</span></a> <a href="https://techhub.social/tags/Grafana" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Grafana</span></a> <a href="https://techhub.social/tags/EvidentlyAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>EvidentlyAI</span></a> <a href="https://techhub.social/tags/Observability" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Observability</span></a> <a href="https://techhub.social/tags/Performance" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Performance</span></a> <a href="https://techhub.social/tags/DataVisualization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataVisualization</span></a></p>
KeyeoH<p>Question about R, mlflow and models...</p><p>I am trying to register a R model using the crate flavor in mlflow, and I have some doubts. </p><p>I have been able to log and register the model. I have also tested that I can load the model again and use it for prediction (inputs/outputs are data.frames).</p><p>I was thinking... that would mean I should write the inference part in R, wouldn't it? </p><p>How could I deploy the model so it can be served as a general web service (REST API), not actually relying on final users to use R? </p><p>I'm now quite tired, but the only solution I have found is to maybe use plumbr to expose an API receiving a JSON with all the inputs as simple types, and generating the data.frame inside, as I have always done. </p><p>Do you think this can be done directly using a crated function? Has anybody done something similar?</p><p>Thanks in advance. I think this is a discussion worth having, as there is a lack of documentation on this topic for us R users. :(</p><p><a href="https://qoto.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://qoto.org/tags/ml" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ml</span></a> <a href="https://qoto.org/tags/machinelearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>machinelearning</span></a> <a href="https://qoto.org/tags/models" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>models</span></a> <a href="https://qoto.org/tags/mlflow" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>mlflow</span></a> <a href="https://qoto.org/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ai</span></a> <a href="https://qoto.org/tags/datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>datascience</span></a> <a href="https://qoto.org/tags/data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>data</span></a> <a href="https://qoto.org/tags/prediction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>prediction</span></a> <a href="https://qoto.org/tags/mlops" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>mlops</span></a> <a href="https://qoto.org/tags/modeldeployment" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modeldeployment</span></a></p>
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