neptune.ai
Algorithmia
Comet.ml
Weights & Biases
Managed MLflow
Spell
MCenter
5Analytics
Papers with Code
ML5.js
Amazon Machine Learning
Lobe
Machine Learning Playground
arXiv
mlblocks
Spell
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 Papers with CodeOnly 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
Based on our record, Papers with Code should be more popular than neptune.ai. It has been mentiond 97 times since March 2021. 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.
Experiment tracking tools like MLflow, Weights and Biases, and Neptune.ai provide a pipeline that automatically tracks meta-data and artifacts generated from each experiment you run. Although they have varying features and functionalities, experiment tracking tools provide a systematic structure that handles the iterative model development approach. - Source: dev.to / 14 days ago
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 / 4 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 / 8 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: 10 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 / 10 months ago
Adapting to Evolving Standards: With the rapid progress in deep learning research and applications, staying current with the latest developments is crucial. The checklist underscores the importance of considering established standard architectures and leveraging current state-of-the-art (SOTA) resources, like paperswithcode.com, to guide project decisions. This dynamic approach ensures that projects benefit from... - Source: dev.to / 4 days ago
Papers With Code is one of the good resources to get you to get started. - Source: dev.to / 2 months ago
For ML/DL papers you can check https://paperswithcode.com/. - Source: Hacker News / 6 months ago
This resource has been invaluable to me: https://paperswithcode.com/ From the past examples you give it sounds like you were into computer vision. There’s been a ton of developments since then, and I think you’d really enjoy the applications of some of those classic convolutional and variational encoder techniques in combination with transformers. A state of the art multimodal non-autoregressive neural net model... - Source: Hacker News / 6 months ago
And also you can find papers with their implementations in code here: http://paperswithcode.com. - Source: Hacker News / 6 months ago
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.
ML5.js - Friendly machine learning for the web
Comet.ml - Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.
Amazon Machine Learning - Machine learning made easy for developers of any skill level
Weights & Biases - Developer tools for deep learning research
Lobe - Visual tool for building custom deep learning models
