Flyte is a workflow automation platform for complex, mission-critical data and ML processes at scale. It has been battle-tested at Lyft, Spotify, Freenome, and others.
Subscribe to our newsletter and never miss any upcoming articles
Building a Weather Forecasting Application with Flyte, Pandera, and Streamlit This is the first in a series of flyte.org projects that demonstrate an end-to-end application using Flyte as one of the components. All of the source code for this project...
This blog is with reference to a talk titled “Self-serve Feature Engineering Platform Using Flyte and Feast”, which was presented by Ketan Umare and Felix Wang at OSPOCon 2021, Seattle. Feature engineering is one of the greatest challenges in applied...
Open-source is growing fast, so are its contributors. At Flyte, we have had meaningful contributions from many contributors who have helped us improve Flyte’s codebase and made us think through unseen perspectives. We have always wanted to have more ...
We’re excited to announce a new integration between Great Expectations and Flyte. We believe this is a much deeper and intuitive integration than ever before! Great Expectations is a Python-based open-source library for validating, documenting, and p...
We all love “undoing” when things don’t work as expected. Imagine the pain we would have to experience without such an option; we can’t just revert to or pull from what we have been working on before. From the perspective of machine learning or data...
MapReduce is a prominent terminology in the Big Data vocabulary owing to the ease of handling large datasets with the “map” and “reduce” operations. A conventional map-reduce job consists of two phases: one, it performs filtering and sorting of the d...
