neptune.ai VS Codeception
Compare neptune.ai VS Codeception and see what are their differences
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neptune.ai
Algorithmia
Comet.ml
Spell
MCenter
5Analytics
Managed MLflow
Numericcal
Codeception
PHPUnit
TestMu AI (Formerly LambdaTest)
CrossBrowserTesting
TestingWhiz
Selenium
Behat
Sauce Labs
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 CodeceptionOnly 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 Codeception. It has been mentiond 24 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.
Some tools for model validation include Neptune AI, Kolena, and Censius. - Source: dev.to / over 1 year 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 / over 2 years 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 / over 2 years 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 / almost 3 years 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: about 3 years ago
Personal experience: - don’t use Behat unless you really needed a “story telling”, it has a intermediate layer Gherkin that you’ll need to code. You can write “Given/When/Then” steps but you’ll also need to write “php code” that will interpret this step. - using real browser be prepared for instability - any interaction with JavaScript can broken/delay execution - be prepared that this tests are call functional... Source: over 3 years ago
Codeception: https://codeception.com/. Source: over 3 years ago
I would say to check out Codeception. Codeceptions has modules for Symfony and database generally. Long and short of it is that if you want you can run api tests that go into the controllers and rollback the database afterwards. Source: almost 4 years ago
There are enough blog posts about Jest or Cypress already, so let me introduce Codecept. It comes in two flavors. There is Codeception for PHP, and there is CodeceptJS for JavaScript which we will be using here. - Source: dev.to / about 4 years ago
There are many tools you can use for this purpose, but one I particularly like is CodeCeption. What I like most about it is that it's a unified tool that can be used to perform several types of tests, acceptance being one of them. - Source: dev.to / about 4 years 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.
PHPUnit - Application and Data, Build, Test, Deploy, and Testing Frameworks
Comet.ml - Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.
TestMu AI (Formerly LambdaTest) - World’s first full-stack Agentic AI Quality Engineering platform.
Spell - Deep Learning and AI accessible to everyone
CrossBrowserTesting - Browser Testing made simple! Run automated, visual, and manual tests on 1500+ real browsers and mobile devices. Test more browsers, in less time.