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]
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
Data privacy issues are among the hottest topics with the most active research in the machine learning space. This is not surprising, since almost every… Read More »Privacy-aware Machine Learning [Part I]: Data Access Protocols
At Simiotics, we’ve started using AWS Lightsail instances to deploy prototypes, proofs of concept, and services that don’t need to scale even in production. It’s… Read More »Using GitHub Actions to deploy to AWS Lightsail
At Bugout, we are heavy users of the GitHub API. We primarily use it for data analysis. GitHub’s personal access tokens have worked really well… Read More »How To Build a GitHub App: Step-by-step instructions