Dashboards for different stages of the ML project + other resources

Dashboards for different stages of the ML project + other resources

Happy to deliver the first portion of ML and MLOps resources in 2023. Here are the best articles, case studies, and interviews that we published (or refreshed or came across) this month. Let me know what you think. 

Case studies & practical MLOps

Building Visual Search Engines - This month, I'll start by bringing up a Q&A with Jakub Cieslik , a Data Scientist with almost 10 years of experience building AI products. If there's anything you want to know about building visual search engines - check this article. 

SwirlAI Newsletter: What's in Kubernetes for MLOps? - I'm plugging in another newsletter within our newsletter, but I figured you might like it. The author, Aurimas Griciūnas Griciūnas, recently joined Neptune as a Solutions Architect, so we're super happy about it. But apart from that, he shares a ton of MLOps knowledge in his emails. So you should definitely check them out. 

Dashboards for Different Stages of the ML Project - Here's an example project we prepared at neptune.ai to showcase how people can use our custom dashboards in the Neptune app. It should be useful to anyone working on ML projects and wondering how to track all the metadata.

No alt text provided for this image
One of the example dashboards

Building a Sentiment Classification System With BERT Embeddings - In this one, Gourav Singh Bais , a Data Scientist at Allianz, shares his lessons learned when building sentiment classification models. He talks about dealing with multilingual data, potential bias, using pre-trained models, deployment, and more.

---

Guides & tutorials

Model Monitoring for Time Series - If you work with time series data, this one can be interesting (and useful). Nilesh Barla prepared a guide that shows how to monitor different things (like learning curves, hardware metrics, data & model drift, etc.) when building and deploying a time series-based model. 

---

Tools

How to Version Control Data in ML for Various Data Sources by Enes Zvorničanin

Kedro vs ZenML vs Metaflow: Which Pipeline Orchestration Tool Should You Choose? by Ricardo Raspini Motta

How to Make Your Sacred Projects Easy to Share and Collaborate On by Aayush Bajaj

---

Q&As with ML practitioners

In February, we have two MLOps Live Q&As planned! We'll talk about:

Managing data and machine learning teams to deliver value with Delina I. , Director of Analytics at Mistplay - February 14, 2023

No alt text provided for this image

What does GPT-3 mean for the future of MLOps? with David Hershey , VP at Unusual Ventures - February 28, 2023 

You can register here to have all of them on the calendar. Or you can just watch them live on Neptune's Linkedin profile

Also, to catch up with previous episodes, go to YouTubeSpotify, or Apple Podcasts

---

Okay, that's it for today. If you want to talk about these recommendations, send us an email or join the MLOps community here, and find the #neptune-ai channel there.

Feel free to forward this newsletter to your friends and communities if you find it useful!

Cheers!

Aurimas Griciūnas

Founder & CEO • AI Engineer • Follow me to Learn about AI Systems • Author of SwirlAI Newsletter • Public Speaker

1y

Super hyped to be part of the team and thank you for the shout-out! :)

To view or add a comment, sign in

Insights from the community

Others also viewed

Explore topics