bytehub
covalent
Our great sponsors
| bytehub | covalent | |
|---|---|---|
| 3 | 4 | |
| 57 | 689 | |
| - | 8.6% | |
| 0.0 | 8.9 | |
| almost 3 years ago | 15 days ago | |
| Python | Python | |
| GNU General Public License v3.0 only | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
bytehub
- [D] Your 🫵 Preferred Feature Stores?
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ByteHub: simple timeseries data preparation in Python
Hi everyone! We’ve been building a Python-based feature-store called ByteHub. The aim is to make time series data easy to store, access, and transform when building machine-learning models. It’s available as an open-source library or as a low-cost cloud-hosted service.
- Show HN: Easy-to-use feature store for ML
covalent
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Remote execution of code
Pretty interesting request, if SSH is not used, i would try using something like dask which uses tcp to connect and execute assuming your workers are in another machine.I also think something like covalent can be used to extend your own custom plugin in their ecosystem to connect how you want. We have a very custom private plugin written on top of covalent's to have a custom protocol to connect our central on-prem GPU machines to our local laptops that is rpc based, mostly for high performance as well as some mandate security from where the GPU machines are. Once done it is pretty much something like
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Prefect alternatives meant for Slurm (HPC)
Does anyone here have any suggestions of alternatives tailored for Slurm on HPC? I know Covalent is one option, but I'm curious about others as well. Ideally the platform should be Pythonic, have a GUI, and be reasonably active/well-maintained.
- Show HN: Covalent – distributed computing for ML, HPC and Quantum (open source)
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Your strategies for offloading computation
Came across this new tool exactly for this - https://github.com/AgnostiqHQ/covalent
What are some alternatives?
feathr - Feathr – A scalable, unified data and AI engineering platform for enterprise
SmartSim - SmartSim Infrastructure Library.
fugue - A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
kestra - Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.
OpenMLDB - OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.
cadence-python - Python framework for Cadence Workflow Service
Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
mlnotify - 🔔 No need to keep checking your training - just one import line and you'll know the second it's done.
prosto - Prosto is a data processing toolkit radically changing how data is processed by heavily relying on functions and operations with functions - an alternative to map-reduce and join-groupby
dagster - An orchestration platform for the development, production, and observation of data assets.
featureform - The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
streetdensityai - This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their coordinates and detected labels.