:rocket: Build and manage real-life data science projects with ease!
Reading up on TFX (https://www.tensorflow.org/tfx/guide): it is written in python and thus (IMO) cannot cover infrastructure aspects. I feel that it somewhat compares to Metaflow (https://metaflow.org/). As I have read more about Metaflow than TFX I'll keep going with Metaflow. It's a python sdk to streamline your ml pipeline wrapping your python annotated code in nodes of a DAG that can be scheduled on your infrastructure (see: https://admin-docs.metaflow.org/metaflow-on-aws/deployment-guide/manual-deployment).
AWS Summit 2022 Australia and New Zealand - Day 2, AI/ML Edition
1 project | dev.to | 20 May 2022
Simplest way to run large batch jobs in the cloud?
1 project | reddit.com/r/dataengineering | 19 Feb 2022
2 projects | news.ycombinator.com | 23 Jan 2022
A few reasons why internal product management is awesome and not a downgrade
1 project | reddit.com/r/ProductManagement | 23 Aug 2021
[D] ML Devs: What are your biggest pain-points when it comes to your data pipeline (i.e. collection, storage, processing, standardizing, etc.)? How do you currently solve them?
2 projects | reddit.com/r/MachineLearning | 2 Sep 2021