iko.ai
JarvisLabs.ai
Censius.ai
Vast.ai
Evidently AI
Bifrost Data Search
ML Showcase
Lightly AI
neptune.ai
Algorithmia
Comet.ml
Weights & Biases
Managed MLflow
Spell
MCenter
5Analytics
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.
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Only 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, neptune.ai should be more popular than iko.ai. It has been mentiond 23 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.
We built a fascinating platform, https://iko.ai, that allows you to train, track, package, deploy, and monitor machine learning models with real-time collaborative notebooks on your own Kubernetes clusters. Source: almost 2 years ago
Hi, Edwin. I'm in the process of integrating Stripe to https://iko.ai. I recently discovered Portal (https://stripe.com/docs/billing/subscriptions/integrating-customer-portal) and I thank you for that. Less code for me. I'm a bit ashamed to say, but I'm having trouble with checking if the customer has a valid subscription. I'm currently only storing the customer_id in the database and retrieving the information... - Source: Hacker News / about 2 years ago
That was one the reasons we do "bring your own compute" with https://iko.ai so people who already have a billing account on AWS, GCP, Azure, DigitalOcean, can just get the config for their Kubernetes clusters and link them to iko.ai and their machine learning workloads will run on whichever cluster they select. If you get a good deal from one cloud provider, you can get started quickly. It's useful even for... - Source: Hacker News / about 2 years ago
We built an internal platform to streamline this that allows us to train, package, deploy, and monitor models (very shameless plug for our product https://iko.ai that we started because I was tired of watching colleagues look from the window to see if their train was here because they had to come to the office to train their model on the "powerful machine" and they spent 6 hours in commute every day and at some... Source: about 2 years ago
We built https://iko.ai which offers real-time collaborative notebooks to train, track, package, deploy, and monitor machine learning models. Source: over 2 years ago
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 / about 1 month 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 / 5 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 / 9 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 / 11 months ago
JarvisLabs.ai - Let's make AI simple
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.
Censius.ai - Building the future of MLOps
Comet.ml - Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.
Vast.ai - GPU Sharing Economy: One simple interface to find the best cloud GPU rentals.
Weights & Biases - Developer tools for deep learning research
