zenml
Tailwind CSS
zenml | Tailwind CSS | |
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33 | 1,281 | |
3,674 | 78,568 | |
2.2% | 1.2% | |
9.8 | 9.4 | |
4 days ago | 3 days ago | |
Python | TypeScript | |
Apache License 2.0 | MIT License |
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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[P] ZenML: Build vendor-agnostic, production-ready MLOps pipelines
GitHub: https://github.com/zenml-io/zenml
- Show HN: ZenML – Portable, production-ready MLOps pipelines
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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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How to improve your experimentation workflows with MLflow Tracking and ZenML
The best place to see MLflow Tracking and ZenML being used together in a simple use case is our example that showcases the integration. It builds on the quickstart example, but shows how you can add in MLflow to handle the tracking. In order to enable MLflow to track artifacts inside a particular step, all you need is to decorate the step with @enable_mlflow and then to specify what you want logged within the step. Here you can see how this is employed in a model training step that uses the autolog feature I mentioned above:
- ZenML helps data scientists work across the full stack
Tailwind CSS
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How to Build Your Own ChatGPT Clone Using React & AWS Bedrock
Finally, for our front end, we’re going to be pairing Next.js with the great combination of TailwindCSS and shadcn/ui so we can focus on building the functionality of the app and let them handle making it look awesome!
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Building an Email Assistant Application with Burr
You can use any frontend framework you want — react-based tooling, however, has a natural advantage as it models everything as a function of state, which can map 1:1 with the concept in Burr. In the demo app we use react, react-query, and tailwind, but we’ll be skipping over this largely (it is not central to the purpose of the post).
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Shared Data-Layer Setup For Micro Frontend Application with Nx Workspace
Tailwind CSS: A utility-first CSS framework for rapidly building custom designs.
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Preline UI + Gowebly CLI = ❤️
First, you need to make sure that you have a working Tailwind CSS project…
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Customer service pages for e-commerce built with Tailwind CSS
Tailwind CSS
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The best testing strategies for frontends
With better CSS approaches like TailwindCSS and Vanilla Extract (which we're heavily using) it's much easier to maintain the UI and make sure it doesn't change unexpectedly. No more conflicting CSS classes, much less CSS specificity issues and much less CSS code in general.
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ChatCrafters - Chat with AI powered personas
This app was built with Svelte Kit, Tailwind CSS, and many other technologies. For a full rundown, please visit the GitHub repository
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Mojo CSS vs. Tailwind: Choosing the best CSS framework
Unlike Tailwind, which has over 77,000 stars on GitHub, Mojo CSS has about 200 stars on GitHub. But the Mojo CSS documentation is fairly good and you can find most of the information you’ll need there.
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Collab Lab #66 Recap
JavaScript React Flowbite Tailwind Firebase - Auth, Database, and Hosting Vite
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Show HN: Brutalisthackernews.com – A HN reader inspired by brutalist web design
- Performance is a feature.
Another common interpretation of brutalism is aesthetic, reacting to overly complicated user interfaces by creating simpler, more direct ones. Tailwind CSS (https://tailwindcss.com), one of today's most popular CSS libraries, promotes this approach in its component examples. There's also a neat library I've seen recently called "Neobrutalism Components" for React that I like (https://neobrutalism-components.vercel.app), providing components with a similar look and feel to Gumroad. This might more accurately be called 'Neo-Brutalism,' as noted in the comments.
A more engineering-centric interpretation of Brutalism focuses on form, structure, and efficiency, drawing significantly from brutalist architecture principles. Apart from the user interface itself, most mobile, desktop, and web applications are extremely bloated and often perform worse than sites from 10 years ago did. While one HTML file might be "less brutalist" than the original HN site, it is substantially more brutalist than any HN mobile app in existence, and offers nearly identical functionality.
A broader interpretation of brutalism, which could be termed 'Meta-Brutalism,' is embodied in the overall experience on this site through UX flows. Yes, in the strictest sense, the original HN site is more Brutalist in many ways, but it only shows 30 articles at a time and does not function as a PWA. For this site, the experience of reading 10 stories is arguably less brutalist, but for quickly browsing through several pages and skimming articles (which is how I read HN) it is a lot faster, and in my opinion, more Brutalist.
My primary inspiration was addressing software and tool bloat in UIs rather than strictly adhering to every principle set forth by David Bryant Copeland. I don't find it convincing that this site "isn't brutalist" compared to really any other experience apart from the Main HN site, and I would argue the overall experience is more brutalist in its performance and scrolling behavior.
As a side note: I generally don't like Brutalist architecture that much although I believe it is unfairly maligned. I visited the Salk Institute once and enjoyed it though (https://www.archdaily.com/61288/ad-classics-salk-institute-l...).
What are some alternatives?
MLflow - Open source platform for the machine learning lifecycle
flowbite - Open-source UI component library and front-end development framework based on Tailwind CSS
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
antd - An enterprise-class UI design language and React UI library
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
unocss - The instant on-demand atomic CSS engine.
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
windicss - Next generation utility-first CSS framework.
Poetry - Python packaging and dependency management made easy
emotion - 👩‍🎤 CSS-in-JS library designed for high performance style composition
pulsechain-testnet
Material UI - Ready-to-use foundational React components, free forever. It includes Material UI, which implements Google's Material Design.