sematic
aqueduct
Our great sponsors
| sematic | aqueduct | |
|---|---|---|
| 4 | 2 | |
| 942 | 521 | |
| 1.1% | 1.0% | |
| 8.7 | 8.7 | |
| 14 days ago | 11 months ago | |
| Python | Go | |
| GNU General Public License v3.0 or later | 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.
sematic
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This Week In Python
sematic – open-source ML pipeline development platform
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What is “production” Machine Learning?
Check us out at sematic.dev, star us on Github, and join us on Discord to discuss production ML.
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Sematic – an open-source ML pipelining tool built by ex-Cruise engineers
Hi all – We are a team of ex ML Infra engineers at Cruise (self-driving cars) and we spent the last few months building Sematic.
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Build on AWS Weekly - S1 E5 - Containers Containers Everywhere
Sematic, an open-source development toolkit for AI/ML: https://github.com/sematic-ai/sematic
aqueduct
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Aqueduct: Take Data Science to Production
Hi everyone!
We've been working on making data teams more productive with Aqueduct for over a year, and we're really excited to share what we've been building.
There's a large (and growing!) number of programmers in the world who understand data and can solve business problems but don't want to spend their time wrangling low-level cloud infrastructure to get their work into the cloud. The existing MLOps tools that claim to solve this problem have been built by & for software teams, and they're incredibly complicated.
With Aqueduct, we've built a tool that's designed for data teams and abstracts away the underlying infrastructure. Aqueduct has a simple Python API that allows you to define a workflow as a composition of Python functions. Those workflows can be easily connected to data sources and can be run anywhere from your laptop to a Kubernetes cluster in the cloud. Once a workflow's running, Aqueduct has lightweight hooks to compute metrics and run tests over your pipelines to ensure they're producing high-quality results.
To learn more about what we're building, check out our GitHub repo or join our community Slack:
https://github.com/aqueducthq/aqueduct
What are some alternatives?
airy - 💬 Open Source App Framework to build streaming apps with real-time data - 💎 Build real-time data pipelines and make real-time data universally accessible - 🤖 Join historical and real-time data in the stream to create smarter ML and AI applications. - ⚡ Standardize complex data ingestion and stream data to apps with pre-built connectors
llama2.go - LLaMA-2 in native Go
django-prose - Wonderful rich-text editing for your Django project
CortexTheseus - Cortex - AI on Blockchain, Official Golang implementation
clamshell - experimenting with a python based shell
fullnamematchscore-go - Generates a match score of two person names from 0-100, where 100 is the highest, on how closely two individual full names match. The scoring is based on a series of tests, algorithms, AI, and an ever-growing body of Machine Learning-based generated knowledge
python-functown - Helper library for Azure Function programming
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
causalgraph - A python package for modeling, persisting and visualizing causal graphs embedded in knowledge graphs.