Hacker News
- Show HN: Cortex – machine learning infrastructure for developers https://github.com/cortexlabs/cortex 14 comments
- Self-hosted AWS Lambda alternative https://github.com/cortexlabs/cortex 5 comments selfhosted
- Cortex - an open source Lambda alternative written in Go https://github.com/cortexlabs/cortex 6 comments golang
- Cortex - Open source alternative to SageMaker for model serving https://github.com/cortexlabs/cortex 12 comments aws
- Cortex: A free and open source alternative to SageMaker for serving models via AWS https://github.com/cortexlabs/cortex/ 19 comments aws
- Self-hosted ML deployment platform https://github.com/cortexlabs/cortex 5 comments programming
Linking pages
- I built a DIY license plate reader with a Raspberry Pi and machine learning | by Robert Lucian Chiriac | Towards Data Science https://towardsdatascience.com/i-built-a-diy-license-plate-reader-with-a-raspberry-pi-and-machine-learning-7e428d3c7401 185 comments
- How we scaled AI Dungeon 2 to support over 1,000,000 users | by Latitude Team | Medium https://medium.com/@aidungeon/how-we-scaled-ai-dungeon-2-to-support-over-1-000-000-users-d207d5623de9 184 comments
- Why we’re writing machine learning infrastructure in Go, not Python | by Caleb Kaiser | Medium https://towardsdatascience.com/why-were-writing-machine-learning-infrastructure-in-go-not-python-38d6a37e2d76 148 comments
- GitHub - RunaCapital/awesome-oss-alternatives: Awesome list of open-source startup alternatives to well-known SaaS products 🚀 https://github.com/RunaCapital/awesome-oss-alternatives 92 comments
- GitHub - josephmisiti/awesome-machine-learning: A curated list of awesome Machine Learning frameworks, libraries and software. https://github.com/josephmisiti/awesome-machine-learning 58 comments
- Why we do machine learning engineering with YAML, not notebooks | by Caleb Kaiser | Medium https://towardsdatascience.com/why-we-do-machine-learning-engineering-with-yaml-not-notebooks-a2a97f5e04f8 52 comments
- Moving from data science to machine learning engineering | by Caleb Kaiser | Medium https://towardsdatascience.com/moving-from-data-science-to-machine-learning-engineering-68916173eaf3 51 comments
- Don’t learn machine learning. Learn how to build software with ML… | by Caleb Kaiser | Medium https://towardsdatascience.com/dont-learn-machine-learning-8af3cf946214 20 comments
- GitHub - RunaCapital/awesome-oss-alternatives: Awesome list of open-source startup alternatives to well-known SaaS products 🚀 https://github.com/RunaCapital/awesome-oss-alternatives?q= 12 comments
- What software engineers can bring to machine learning | by Caleb Kaiser | Medium https://towardsdatascience.com/what-software-engineers-can-bring-to-machine-learning-25f458c80e5 12 comments
- Should you really use machine learning for that? | by Caleb Kaiser | Towards Data Science https://towardsdatascience.com/should-you-really-use-machine-learning-for-that-d781a80aa0fb 8 comments
- We tried to build an end-to-end ML platform. Here’s why it failed. | by Caleb Kaiser | Medium https://towardsdatascience.com/we-tried-to-build-an-end-to-end-ml-platform-heres-why-it-failed-190c0f503536 4 comments
- GitHub - ahkarami/Deep-Learning-in-Production: In this repository, I will share some useful notes and references about deploying deep learning-based models in production. https://github.com/ahkarami/Deep-Learning-in-Production 2 comments
- Why we’re writing machine learning infrastructure in Go, not Python | by Caleb Kaiser | Medium https://towardsdatascience.com/why-were-writing-machine-learning-infrastructure-in-go-not-python-38d6a37e2d76?gi=dc4596294618 1 comment
- How to run machine learning at scale — without going broke | by Caleb Kaiser | Medium https://towardsdatascience.com/how-to-run-machine-learning-at-scale-without-going-broke-4871993e4724 0 comments
- Lessons learned building an open source machine learning platform | by Caleb Kaiser | Medium https://towardsdatascience.com/lessons-learned-scaling-an-open-source-machine-learning-platform-d616927beb20 0 comments
- GitHub - EthicalML/awesome-production-machine-learning: A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning https://github.com/EthicalML/awesome-production-machine-learning 0 comments
- How to Actually Use ML in Production: Text Classification | by Caleb Kaiser | Medium https://towardsdatascience.com/how-to-actually-use-ml-in-production-text-classification-1e27bb5ac64d 0 comments
- Benchmarking OpenAI’s GPT-2 on GPUs vs. CPUs | by Caleb Kaiser | Medium https://towardsdatascience.com/how-much-difference-do-gpus-make-in-model-serving-c40b885ac096 0 comments
- Why we’re writing machine learning infrastructure in Go, not Python | by Caleb Kaiser | Medium https://towardsdatascience.com/why-were-writing-machine-learning-infrastructure-in-go-not-python-38d6a37e2d76?sk=7c85a8ab2a203c5c62ac41b7183585a1&source=friends_link 0 comments
Linked pages
Related searches:
Search whole site: site:github.com
Search title: GitHub - cortexlabs/cortex: Production infrastructure for machine learning at scale
See how to search.