zenml
handbook
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zenml | handbook | |
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33 | 6 | |
3,638 | 132 | |
2.6% | 3.0% | |
9.8 | 9.9 | |
about 21 hours ago | about 17 hours ago | |
Python | TypeScript | |
Apache License 2.0 | 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.
zenml
- FLaNK AI - 01 April 2024
- What are some open-source ML pipeline managers that are easy to use?
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[P] I reviewed 50+ open-source MLOps tools. Here’s the result
Currently, you can see the integrations we support here and it includes a lot of tools in your list. I also feel I agree with your categorization (it is exactly the categorization we use in our docs pretty much). Perhaps one thing missing might be feature stores but that is a minor thing in the bigger picture.
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[D] Feedback on a worked Continuous Deployment Example (CI/CD/CT)
Hey everyone! At ZenML, we released today an integration that allows users to train and deploy models from pipelines in a simple way. I wanted to ask the community here whether the example we showcased makes sense in a real-world setting:
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How we made our integration tests delightful by optimizing our GitHub Actions workflow
As of early March 2022 this is the new CI pipeline that we use here at ZenML and the feedback from my colleagues -- fellow engineers -- has been very positive overall. I am sure there will be tweaks, changes and refactorings in the future, but for now, this feels Zen.
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Ask HN: Who is hiring? (March 2022)
ZenML is hiring for a Design Engineer.
ZenML is an extensible, open-source MLOps framework to create production-ready machine learning pipelines. Built for data scientists, it has a simple, flexible syntax, is cloud- and tool-agnostic, and has interfaces/abstractions that are catered towards ML workflows.
We’re looking for a Design Engineer with a multi-disciplinary skill-set who can take over the look and feel of the ZenML experience. ZenML is a tool designed for developers and we want to delight them from the moment they land on our web page, to after they start using it on their machines. We would like a consistent design experience across our many touchpoints (including the [landing page](https://zenml.io), the [docs](https://docs.zenml.io), the [blog](https://blog.zenml.io), the [podcast](https://podcast.zenml.io), our social media, the product itself which is a [python package](https://github.com/zenml-io/zenml) etc).
A lot of this job is about communicating complex ideas in a beautiful way. You could be a developer or a non-coding designer, full time or part-time, employee or freelance. We are not so picky about the exact nature of this role. If you feel like you are a visually creative designer, and are willing to get stuck in the details of technical topics like MLOps, we can’t wait to work with you!
Apply here: https://zenml.notion.site/Design-Engineer-m-f-1d1a219f18a341...
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Ask HN: Who is hiring? (January 2022)
ZenML | Developer Advocate | Full-time | Remote (Europe / UK) | [https://zenml.io](https://zenml.io)
Hey! We are an open-source company and the pulse of [ZenML](https://github.com/zenml-io/zenml)'s community is our driving force! ZenML is a MLOps framework to create reproducible ML pipelines for production machine learning use-cases.
As a Developer Advocate / 'Tech Evangelist', you will help us fulfil our mission by connecting with other developers, contributing to open-source, and sharing your knowledge and experience about ZenML and other leading technologies at conferences and meetups, in contributed articles, and on blogs, podcasts, and social media. Your work will foster a community inspired by ZenML and will drive our strategy around developer love and our participation in the open-source ecosystem. You will also be responsible measure engagement with the community, and find creative ways to drive it up.
We focus on generating awareness about ZenML by contributing to the ecosystem and enabling others to become evangelists outside the company as well. Not afraid to be hands-on, you might write sample code, author client libraries, provide insights to journalists, and work with strategic partners, users, and customers to excite and engage our developer communities.
For full details on this role, check out [https://zenml.io/careers/](https://zenml.io/careers/).
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Taking on the ML pipeline challenge: why data scientists need to own their ML workflows in production
ZenML is an open-source MLOps Pipeline Framework built specifically to address the problems above. Let’s break it down what a MLOps Pipeline Framework means:
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Spot the difference in ML costs
If you're looking for a head start for spot instance training, check out ZenML, an open-source MLOps framework for reproducible machine learning. Running spot pipeline in ZenML, is as easy as :
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10 Ways To Level Up Your Testing with Python
There's nothing like working on testing to get you familiar with a codebase. I've been working on adding back in some testing to the ZenML codebase this past couple of weeks and as a relatively new employee here, it has been a really useful way to dive into how things work under the hood.
handbook
- Ask HN: What companies have publicly available handbooks?
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Show HN: 27 Companies hiring software engineers based anywhere in the world
Sorry for the glitchy scrolling issue on our handbook, thank you both for re-raising this, and thank you @niel for the PR (https://github.com/sourcegraph/handbook/pull/6080). I confirmed that the PR fixed it, and I just merged the PR.
Thanks! I'm not directly affiliated.
I see someone at Sourcegraph has been tracking this issue at https://github.com/sourcegraph/handbook/issues/3666
- Artsy Engineering Handbook
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Ask HN: Who is hiring? (January 2022)
My biggest endorsement of Sourcegraph is that on Sunday nights I look forward to getting back to it on Monday morning to work with my amazing team and solve hard problems. I struggled with Sunday scaries at my previous job and I've had nothing like that at Sourcegraph.
I highly encourage you to apply if you have even a passing interest in Sourcegraph. Check out our handbook (https://handbook.sourcegraph.com) where we answer most questions you'll have. Or send me an email and I'd gladly chat with you about the company and how we operate.
What are some alternatives?
MLflow - Open source platform for the machine learning lifecycle
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Poetry - Python packaging and dependency management made easy
pulsechain-testnet
proposals - Temporal proposals
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
budgetml - Deploy a ML inference service on a budget in less than 10 lines of code.
huggingface_hub - The official Python client for the Huggingface Hub.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Fleet - Open-source platform for IT, security, and infrastructure teams. (Linux, macOS, Chrome, Windows, cloud, data center)