Continuous integration services like Jenkins, Bitbucket Pipelines, CircleCI, GitHub Actions, Gitlab CI/CD force extreme automation. They require your continuous integration flows to run non-interactively in… Read More »Break out of the deployment death loop
This is a short note which explains how to set up a GitHub Action to post a comment on a pull request. The GitHub Marketplace… Read More »Commenting on PRs from GitHub Actions
Finance is one of the most regulated industries in the US, which makes application of cutting-end technologies, like artificial intelligence and machine learning, much harder.… Read More »ML Model Risk Management: How to Bring Explainability and Robustness in Production
GPT-3 has generated lots of buzz and attention from the machine learning and AI research communities and diverse opinions about the capabilities of the model. … Read More »How the GPT-3 model works in production
How to store, provide easy access and ensure version control of unstructured data is an open-ended question and is a challenge for more than 200K… Read More »How to mitigate the pain of dataset management
We have a great community of developers on Slack and our goal is to support each other in any way we can: either by providing… Read More »“How to translate ML predictions into practical solutions” by Kaggle Learn creator Dan Becker
We continue to discuss Federated Learning technology and its applications. Check out the first part here where we highlighted FL basics. This part is focused… Read More »Federated Learning Technology Explained: Google’s use case [Part II]
As of July 2020, 4.78 billion people in the world own smartphones. The number of IoT devices on the planet reached 26.66 billion at the… Read More »Federated Learning Technology Explained: Google’s use case [Part I]
“He was spoilt from childhood by the Future, which he mastered rather early and apparently without great difficulty.” When we think of developers in AI,… Read More »Which Python Coders Will Transform AI’s Future?
We are continuing our sequence of articles with practical suggestions on how to build machine learning models without compromising user privacy. In the first article… Read More »Privacy-aware Machine Learning: How To Train ML Models in a Remote Environment [Part II]