Software Alternatives, Accelerators & Startups

ai.dopt VS neptune.ai

Compare ai.dopt VS neptune.ai and see what are their differences

ai.dopt logo ai.dopt

Discover Your AI Potential

neptune.ai logo neptune.ai

Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.
  • ai.dopt Landing page
    Landing page //
    2023-09-30

We enable medium-sized companies to continuously manage their individual AI potential. We provide automated support from the prioritization of relevant applications to their implementation and successful monitoring - and always regardless of the underlying technology and in compliance with the highest security standards. For competitive value creation, today and in the future!

  • neptune.ai Landing page
    Landing page //
    2023-08-24

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

Website
neptune.ai
$ Details
freemium
Platforms
Python
Release Date
2018 April
Startup details
Country
Poland
State
Mazowieckie
City
Warsaw
Founder(s)
Piotr Niedzwiedz
Employees
10 - 19

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neptune.ai videos

Machine Learning Experiment Management with Neptune.ai - How to start

Category Popularity

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Business Process Management
Data Science And Machine Learning
Business Management
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Data Science Notebooks
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Reviews

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ai.dopt Reviews

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neptune.ai Reviews

  1. Easy to use, not overdone, good for model management and collab

    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

Social recommendations and mentions

Based on our record, neptune.ai seems to be more popular. 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.

ai.dopt mentions (0)

We have not tracked any mentions of ai.dopt yet. Tracking of ai.dopt recommendations started around Mar 2023.

neptune.ai mentions (23)

  • A step-by-step guide to building an MLOps pipeline
    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 / 7 days ago
  • A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
    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
  • Show HN: A gallery of dev tool marketing examples
    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
  • How to structure/manage a machine learning experiment? (medical imaging)
    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
  • How to grow a developer blog to 3M annual visitors? with Jakub Czakon (Neptune.ai)
    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
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What are some alternatives?

When comparing ai.dopt and neptune.ai, you can also consider the following products

Obviously.ai - The entire process of running Data Science - building Machine Learning algorithm, explaining results and predicting outcomes, packed in one single click.

Comet.ml - Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.

Mutable.ai - Build together with AI

Weights & Biases - Developer tools for deep learning research

Akkio - No-Code AI models right from your browser

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.