Post
472
🚀 Introducing Goldener: The Python Data Orchestrator for more efficient ML
Machine Learning workflows often rely on randomness: selecting/splitting data for training, batching it variably, and monitoring real-world performance.
Nowadays, foundation models give access to the semantics of data. Goldener leverages this semantic to make the entire ML lifecycle more efficient!
🔗 Check it out: https://github.com/goldener-data/goldener
🔨 Give it a try: pip install goldener
Machine Learning workflows often rely on randomness: selecting/splitting data for training, batching it variably, and monitoring real-world performance.
Nowadays, foundation models give access to the semantics of data. Goldener leverages this semantic to make the entire ML lifecycle more efficient!
🔗 Check it out: https://github.com/goldener-data/goldener
🔨 Give it a try: pip install goldener