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Dasha Maliugina

Dasha Maliugina

Community Manager
Evidently AI
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Explore all blogs by this author

AMA with Lina Weichbrodt: ML monitoring, LLMs, and freelance ML engineering

May 8, 2023

In this blog, we recap the Ask-Me-Anything session with Lina Weichbrodt. We chatted about ML monitoring and debugging, adopting LLMs, and the challenges of being a freelance ML engineer.

Community

AMA with Stefan Krawczyk: from building ML platforms at Stitch Fix to an open-source startup on top of the Hamilton framework

March 19, 2023

In this blog, we recap the Ask-Me-Anything session with Stefan Krawczyk. We chatted about how to build an ML platform and what data science teams do wrong about ML dataflows.

Community

How to build an ML platform? Lessons from 10 tech companies

February 22, 2023

How to approach building an internal ML platform if you’re not Google? We put together stories from 10 companies that shared their platforms’ design and learnings along the way.

MLOps

AMA with Neal Lathia: data science career tracks, shipping ML models to production, and Monzo ML stack

February 6, 2023

In this blog, we recap the Ask-Me-Anything session with Neal Lathia. We chatted about career paths of an ML Engineer, building and expanding ML teams, Monzo’s ML stack, and 2023 ML trends.

Community

50 best machine learning blogs from engineering teams

January 19, 2023

Want to know how companies with top engineering teams do machine learning? We put together a list of the best machine learning blogs from companies that share specific ML use cases, lessons learned from building ML platforms, and insights into the tech they use.

Community

AMA with Ben Wilson: planning ML projects, AutoML, and deploying at scale

December 12, 2022

In this blog, we recap the Ask-Me-Anything session with Ben Wilson. We chatted about AutoML use cases, deploying ML models to production, and how one can learn about ML engineering.

Community

Data Science and Machine Learning conferences to attend in 2023

November 11, 2022

Planning for 2023 and looking for the conferences to attend? We made the research and selected the most interesting events and conferences happening in 2023. And the best part? Some of the conferences are free to attend or publish the content after the event.

Community

AMA with Rick Lamers: the evolution of data orchestration tools and the perks of open source

November 4, 2022

In this blog, we recap the Ask-Me-Anything session with Rick Lamers, where we chatted about the evolution of orchestration tools, their place within the MLOps landscape, the future of data pipelines, and building an open-source project amidst the economic crisis.

Community

How to contribute to open source as a Data Scientist, and Hacktoberfest 2022 recap

November 1, 2022

Now that Hacktoberfest 2022 is over, it’s time to celebrate our contributors, look back at what we’ve achieved together, and share what we’ve learned during this month of giving back to the community through contributing to open source.

Community

AMA with Jacopo Tagliabue: reasonable scale ML, testing recommendation systems, and hot DataOps

September 27, 2022

In this blog, we recap the Ask-Me-Anything session with Jacopo Tagliabue, where we chatted about ML at a reasonable scale, testing RecSys, MLOps anti-patterns, what’s hot in DataOps, fundamentals in MLOps, and more.

Community

AMA with Bo Yu and Sean Sheng: why ML deployment is hard

September 12, 2022

In this blog, we recap the Ask-Me-Anything session with Bozhao Yu and Sean Sheng, where we chatted about why deploying a model is hard, beginner mistakes and how to avoid them, the challenges of building an open-source product, and BentoML’s roadmap.

Community

AMA with Doris Xin: AutoML, modern data stack, and reunifying the tools

August 27, 2022

In this blog, we recap Ask-Me-Anything session with Doris Xin, that covered the roles of Data Scientists and Data Engineers in an ML cycle, automation, MLOps tooling, bridging the gap between development and production, and more.

Community

AMA with Fabiana Clemente: synthetic data, data-centric approach, and rookie mistakes to avoid

July 20, 2022

We recap Ask-Me-Anything session with Fabiana Clemente, which covered synthetic data, its quality, beginner mistakes in data generation, the data-centric approach, and how well companies are doing in getting there.

Community

Which test is the best? We compared 5 methods to detect data drift on large datasets

June 20, 2022

We ran an experiment to help build an intuition on how popular drift detection methods behave. In this blog, we share the key takeaways and the code to run the tests on your data.

ML Monitoring

AMA with Matt Squire: what makes a good open-source tool great, and the future of MLOps

June 15, 2022

In this blog we recap Ask-Me-Anything session with Matt Squire, that covered MLOps maturity and future, how MLOps fits in data-centric AI, and why open-source wins.

Community

AMA with Hamza Tahir: MLOps trends, tools, and building an open-source startup

June 1, 2022

In this blog we recap Ask-Me-Anything session with Hamza Tahir, that covered MLOps trends and tools, the future of real-time ML, and building an open-source startup.

Community

Evidently Community Call #2 Recap: custom text comments, color schemes and a library of statistical tests

May 24, 2022

In this blog we recap the second Evidently Community Call that covers the recent feature updates in our open-source ML monitoring tool.

Community

AMA with Alexey Grigorev: MLOps tools, best practices for ML projects, and tips for community builders

May 10, 2022

In this blog we recap Ask-Me-Anything session with Alexey Grigorev, that covered all things production machine learning, from tools to workflow, and even a bit on community building.

Community

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