Special thanks to @mertbozkirr for leading the Hacktoberfest charge!
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๐น Closure Session 2 event
Our Community Champion @jcpsantiago gave an introduction to DVC in preparation for the remainder of the session where @carsten_behring, author of Metamorph presents how NLP pipelines can be managed with DVC, Closure & Python.
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โพ๏ธ CML at NeurIps
Well, this work will be presented within the virtual Workshop Challenges In Deploying and Monitoring Machine Learning Systems at NeurIps virtual this year on December 9th.
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๐ฌ๐ง MLOps Summit London
We were also part of the MLOps Summit in London!
Aside from attending a variety of great talks, we met many wonderful people from around the world resulting in some really interesting discussions around MLOps.
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๐บ๐ธ ODSC West
We had great conversations with conferencegoers and attended great sessions!
Dmitry had a packed room for his in-person talk Why You Need a GitOps-based Machine Learning Model Registry and Alex Kim presented CI/CD for Machine Learning virtually.
We were privileged to have Matt Squire from @FuzzyLabsAI, a renowned expert in the MLOps space, as our guest.
During the session, Matt shared his insights on the benefits of open-source MLOps tools and how they can help businesses.
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In his ๐ฃ๐ฟ๐ฒ๐๐ฒ๐ป๐๐ฎ๐๐ถ๐ผ๐ป, Matt provided a comprehensive breakdown of the MLOps tool space, categorizing it into SaaS platforms, fully open source, and partly open source tools.
He went on to describe the defining traits of open source and why he believes it to be the best choice for MLOps, including its flexibility, cost-effectiveness, and agility.
Matt's views on open-source MLOps tools generated a lot of engagement from our community members.
Several data practitioners have asked for a tutorial video from us on DVC, and we are glad to make this available.
In this video, you'll discover how to use the DVCLive and @huggingface datasets to create a Tweet Sentiment Analyzer.
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Do you want to learn more about using real-time metrics in machine learning experiments? Look nowhere else!
In this ๐๐๐๐ผ๐ฟ๐ถ๐ฎ๐น, we'll show you how to use DVCLive and the Hugging Face Dataset to build a potent Twitter sentiment analyzer.
๐๐๐๐๐ข๐ฏ๐, a library from ๐๐๐, gives you the ability to easily monitor your ML experiments. You will be able to easily grasp the performance of your model at every stage thanks to its real-time metrics.
We are happy to announce something exciting to the ML/AI Community๐จ
DVC has just released its new integration with Optuna, enabling you to streamline and optimize your hyperparameter search process while keeping track of every step with version control.
Our users have been requesting this integration for a while, and we're thrilled to deliver!
With the DVC's extension for VS Code, you can easily monitor and analyze your results, saving you time and effort in your machine learning workflow.
Try out our new integration today and see the benefits for yourself! ๐
This is the link to the video -
In the video, we explain how to use Optuna with Keras and view each iteration as an experiment in DVC's experiment table and plots. ๐๐
Woah! Been here? Is deep learning model training going horribly wrong? ๐๐ฝโโ๏ธ
Iterative Studio makes this easy to see so you don't waste time and resources!
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With Iterative Studio and DVCLive, you can monitor the progress of your long-running experiments against others that you or your team have performed. All are easily accessed at work, at home, or by the rest of your team on the project.
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You provide a couple environment variables for your model training job:
You can enter your STUDIO_TOKEN and dvc exp run if running locally