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AI and Machine Learning Model Management and Operations for Enterprise Data Science Teams

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Meeta Dash
May 26, 2021
Monitor any model, data or ML pipeline built in any framework with Verta Model Monitoring. Keep track of data drift, outliers and model performance. 
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Meeta Dash
February 18, 2021
MLOps cannot be done right until you have a state-of-the-art Model Registry. What are the 3 reasons why data scientists should worry about Model Registry? 
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Manasi Vartak
December 16, 2020
Managing data science teams successfully is challenging and interesting. The four factors you can take into consideration to promote high team performance. 
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Michael Liu
November 19, 2020
Is serverless the right compute architecture to deploy models? Pros & cons of a system like Verta for inference that abstracts away infrastructure complexity.  
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Manasi Vartak
November 19, 2020
This is a summary of our blog series on Serverless Inference for ML models for KubeCon 2020 talk: Serverless for ML Inference on Kubernetes: Panacea or Folly? 
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John Dean
November 13, 2020
Is serverless is the right paradigm to deploy models? How to get started with deploying models on Google Cloud Run, pros & cons of using it for inference. 
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Conrado Silva Miranda
November 12, 2020
AWS Lambda is AWS’s serverless offering & arguably the most popular cloud-based serverless framework. An analysis on whether to use it for ML inference. 
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Manasi Vartak
August 21, 2020
Verta Model Management and Operations platform launch and our $10M Series A funding led by Intel Capital. We help data science teams to tame the ML chaos. 
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Conrado Silva Miranda
August 21, 2020
We have gotten good at creating models and iterating on them, but most companies still don't use them well. Why are companies struggling to operationalize ML? 
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Conrado Silva Miranda
June 5, 2020
Git has by now become the defacto standard for versioning your code. However, machine learning is still figuring out how to leverage the benefits it brings. 
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Manasi Vartak
May 13, 2020
A recap of my ML in Product Talk at the Strata OReilly Superstream that covers topics like what is MLOps, building an MLOps pipeline & real-world simulations. 
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Manasi Vartak
April 7, 2020
At Verta, we ran our ModelDB 2.0 launch webinar last week. This blog post is a recap of the hands-on tutorial part of the webinar with Scikit-learn example. 
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Conrado Silva Miranda
March 9, 2020
Since we wrote ModelDB 1.0, a pioneering model versioning system, we have learned a lot and today we are excited to announce the launch of ModelDB 2.0. 
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Conrado Silva Miranda
January 17, 2020
ML environments are a rich target for attackers like the cryptomining campaign attack. Here's my advice on why this problem is hard & what you can do about it.  
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Manasi Vartak
November 26, 2019
After successfully implementing Verta, LeadCrunch sped up model production 5X and now deploys models monthly. Here's how they did it with Verta MLOps. 
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Manasi Vartak
October 7, 2019
At the inaugural TWIMLCon in San Francisco, I led a session on whether to build ML infrastructure in-house, whether to buy or just leverage open-source. 
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Manasi Vartak
October 3, 2019
The future is intelligent and models are the new code. At Verta.AI, we are building software in the service of models and the teams that develop them.  
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Manasi Vartak
October 3, 2019
Let's talk about an often-overlooked but a critical issue in ML, without which we cannot trust models to run our products. We talk about model versioning. 
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