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.
Databox pulls all your data into one place, so you can track performance and discover insights in real-time.
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 Databox. 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.
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 / 9 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
Databox — Business Insights & Analytics by combining other analytics & BI platforms. Free Plan offers 3 users, dashboards & data sources. 11M historical data records. - Source: dev.to / 4 months ago
You need a plan that gives you access to workflows, and the ad events tool. If you can also get the lower tier of a paid databox subscription for reporting. Source: over 1 year ago
I've actually just read about this service on another post, but if it's just a way to display the data from a Google Ads account that makes it easy to interpret and to share then you can get a free account here: https://databox.com. Source: over 1 year ago
Another option is to go with something like https://databox.com/ with built-in reporting. $250 just to white label the reports seems excessive though. Source: over 1 year ago
Databox — Business Insights & Analytics by combining other analytics & BI platforms. Free Plan offers 3 users, dashboards & data sources. 11M historical data records. - Source: dev.to / almost 3 years ago
Comet.ml - Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.
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Weights & Biases - Developer tools for deep learning research
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