neptune.ai
Comet.ml
Algorithmia
Weights & Biases
Managed MLflow
Spell
MCenter
Iterative.ai
Gradio
Streamlit
Hugging Face
Anvil.works
Shuffle.dev
PyTorch
Atom
DuckDuckGo
Track and version your notebooks Log all your notebooks directly from Jupyter or Jupyter Lab. All you need is to install a Jupyter extension.
Manage your experimentation process Neptune tracks your work with virtually no interference to the way you like to do it. Decide what is relevant to your project and start tracking: - Metrics - Hyperparameters - Data versions - Model files - Images - Source code
Integrate with your workflow easily Neptune is a lightweight extension to your current workflow. Works with all common technologies in data science domain and integrates with other tools. It will take you 5 minutes to get started.
neptune.ai GradioOnly negative is I didn't see it integrated with Azure, does with Google, AWS and one more. Looks real nice, and pretty powerful and plenty useful features for a data science group
Gradio might be a bit more popular than neptune.ai. We know about 27 links to it since March 2021 and only 22 links to neptune.ai. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Neptune.ai - Log, store, display, organize, compare, and query all your MLOps metadata. Free for individuals: 1 member, 100 GB of metadata storage, 200h of monitoring/month. - Source: dev.to / 3 months ago
Hi I am Jakub. I run marketing at a dev tool startup https://neptune.ai/ and I share learnings on dev tool marketing on my blog https://www.developermarkepear.com/. Whenever I'd start a new marketing project I found myself going over a list of 20+ companies I knew could have done something well to “copy-paste” their approach as a baseline (think Tailscale, DigitalOCean, Vercel, Algolia, CircleCi, Supabase,... - Source: Hacker News / 7 months ago
There are a lot of tools out there for experiment tracking (eg neptune.ai), but I'm really not sure whether that sort of thing is over the top for what I need to do. Source: 8 months ago
Welcome to another episode of The Developer-led Podcast, where we dive into the strategies modern companies use to build and grow their developer tools. In this exciting episode, we're joined by Jakub Czakon, the CMO at Neptune.ai, a startup that assists developers in efficiently managing their machine-learning model data. Jakub is renowned not only for his role at Neptune.ai but also for his developer marketing... - Source: dev.to / 9 months ago
Tbh I have done a pretty good search on this topic, I couldn't find any. I thought maybe community could help me find one, if people like you (who works at neptune.ai) have the same opinion then it is what it is :). Anyway thank you for the suggestions that you gave, probably gonna use that. Source: 10 months ago
We can quickly leverage our python knowledge to implement and deploy a text summarization chatbot, using pretrained AI models and the frontend framework I already described several times, gradio. - Source: dev.to / 1 day ago
Current version of the "AI battleground" is super shit, this is largely because I picked the wrong framework to build it (gradio.app -- it's good for prototyping but terrible for production, as I've learned). The game-plan is to bring this in-app over the next 2 weeks. Latency will be improved and UX should be a lot better. Bear with us, lots of exciting stuff in the pipeline (audio for ultra, new way for us to... Source: 11 months ago
We've been building devtools for years now. We're really passionate about the field. The most recent thing we built is https://usedevbook.com. The goal was to build a simple framework/UI for companies to demo their APIs. Something like https://gradio.app but for API companies. It's been used for example by Prisma - we helped them build their playground with it - https://playground.prisma.io/ Our new project - e2b... - Source: Hacker News / about 1 year ago
I assume GP is referring to frameworks like Gradio (https://gradio.app/) and to a lesser extent Streamlit. Existing web UI frameworks for Python are somewhat opinionated around particular use cases, of which AI/ML is a prominent one. - Source: Hacker News / about 1 year ago
For making the UI I would recommend that you check out Gradio, it's a fantastic library that allows you to make UI for your ml projects _^. Source: about 1 year ago
Comet.ml - Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.
Streamlit - Turn python scripts into beautiful ML tools
Algorithmia - Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.
Hugging Face - The Tamagotchi powered by Artificial Intelligence 🤗
Weights & Biases - Developer tools for deep learning research
Anvil.works - Build seriously powerful web apps with all the flexibility of Python. No web development experience required.
