Datatron

Datatron provides an enterprise-grade MLOps & AI model governance platform (de-coupled ) w/ model catalog for all of your AI/ML production models

[Slazac 🇪🇺🇺🇦🇹🇼🌐 @TrueSlazac]

Every official photo of the Swiss federal council since 2000

Starting with 2025:

[Datatron @datatron]

@meheller I've enjoyed your articles. When are you planning on doing your next #mlops article?

[Datatron @datatron]

#datascientists #mlengineers You can only solve something when you acknowledge that there is an issue. What's your #mlops maturity? Gauge the maturity of your #ai #ml program across Ideation, Team, Stack, Process, & Outcome in this informative infographic.
https://t.co/IwC73E2Ian

[Datatron @datatron]

@mattturck wanted to make sure to get @datatron #ml #deployment #platform added to updated 2022 https://t.co/ChPeCbZzd1 as industry moves to a hybrid build-and-buy and cloud and on-prem best practice...we are well positioned.

[Datatron @datatron]

@chipro I really enjoyed your article, but @datatron needs updating as we focus on deployment. DM me so I can share. https://t.co/JsgtJgbf0q

[Datatron @datatron]

@datatron is proud to announce our latest release
"Datatron 3.0" is now on @ProductHunt - #JupyterHub, #Kubernetes, and more...Check it out and we'd kindly appreciate upvotes. 😉 👍https://t.co/Iawr91OSYS

[Datatron @datatron]

Datatron President Victor Thu is quoted in Protocol article discussing how companies are deciding between running #ml models on-prem or in the cloud. A very insightful article...
https://t.co/UDPn3SuYDd

#machinelearning #datascience #artificialintelligence #mlops

[Datatron @datatron]

Free #mlops webinar starting now *** No Registration required ***. See the features that leading enterprises are demanding. #datascientists streamline workflows via #jupyterhub integration.

JOIN US NOW! No sign-up required. Just click below!

https://t.co/aG3QfAOg3A

[Datatron @datatron]

*** Today *** is the day. Datatron is hosting our "Datatron 3.0" Product Release Webinar. Starts at 11 am PT. You won't want to miss it! And if you do, we'll email you the recording link. Register Now! #ml #machinelearning #ArtificialIntelligence

https://t.co/jVpoWYAhr2

[Datatron @datatron]

Join us as tomorrow (Tues) 7/26 for our "Datatron 3.0" product release webinar and learn about our #jupyternotebook #jupyterHub integration, simplified #kubernetes mgmt. and more enterprise features. #ml #DataScience #MLOps #mlopsplatform # Register:
https://t.co/YEQqc6sLGn

[Datatron @datatron]

#datascientist are you using #jupyternotebook #jupyterhub? Our new integration, part of our "Datatron 3.0" #datatron30 release, allows you to upload, share & deploy your #ml #machinelearning models directly from your #notebook. #mlops #pytorch #tenstorflow https://t.co/VZjuGz1GA9

[Datatron @datatron]

Are you a #datascientist working in #jupyterhub #jupyternotebook? Check out Datatron's new integration - upload, download, deploy and share #MachineLearning models all from within the Notebook interface with which you are already familiar! https://t.co/VZjuGz1GA9

[Datatron @datatron]

#mlops #platform Datatron is proud to announce our latest release "Datatron 3.0" #datatron30 which includes a #jupyterhub #jupyternotebook integration, simplified #kubernetes management for #machinelearning. Check out the release notes https://t.co/VZjuGz1GA9

[Victor Thu @VictorThu]

A9: Fail fast with AI.
This is a different mindset that’s different from traditional software. You need to deploy your AI in production so that you can learn quickly and make the appropriate adjustments. All the trainings in the lab will do ... #eweekchat https://t.co/EhMVbS3BZF

[Victor Thu @VictorThu]

A8: The economy today is a good forcing function for enterprises to stop treating AI like a toy.

In 3 to 5 years, enterprises who pivoted from building their own tools will advance much rapidly as they focus on delivering real results rather... #eweekchat https://t.co/MSTlzHhmfe

[Victor Thu @VictorThu]

A5: The biggest myth is that data scientists strongly believe their models are so unique that no commercial software can handle their unique properties.

This is not the case, and it stems from a knowledge gap that exists between teams. #eweekchat https://t.co/yTziaUcNnq

[Victor Thu @VictorThu]

And the other thing is, don't fall in love with super high accuracy with your models. Sometimes the actual business results between 80% accuracy and 90% accuracy is not material. It's better to just deploy them! #eweekchat https://t.co/N8mquH923R

[Victor Thu @VictorThu]

A4: Start with the fundamental. What business problem are you trying to solve and why AI. Some business challenges may not require sophisticated AI models. #eweekchat https://t.co/lYs9eiUzZw

[Victor Thu @VictorThu]

A3: 1) The over-romanticization of free open-source tools to deploy AI/ML. It’s hampering enterprises from getting any real ROI.
2) The scarcity of talents and the difficulties of hiring the right talents. #eweekchat https://t.co/qOrNM0rBBE

[Victor Thu @VictorThu]

Yes, @JamesMaguire, there's definitely a sense of concern especially the lack of ROI with such a huge investment. So if a large company is struggling, the smaller ones will feel the pain even more acutely. #eweekchat https://t.co/C2Yb1nuGcN