
WebCatalog
Fluid
Nativeifier
Rambox
Franz
Firework
Multi
Arc
Count
Apple Machine Learning Journal
Comet.ml
ML Showcase
Paperspace Gradient
ModelDepot
OpenAI Universe
ML5.js
WebCatalog
CountNo features have been listed yet.
WebCatalog is recommended for individuals who work with multiple web applications regularly and prefer a desktop-like experience for their web apps. It is particularly useful for professionals, remote workers, and tech enthusiasts who want to streamline their web app usage while maintaining privacy and productivity.
Based on our record, WebCatalog seems to be more popular. It has been mentiond 12 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.
Usually also is supported some type of customization at css level, menus, spaces, notifications, faceid... Take a look at webcatalog software https://webcatalog.io/en/. Source: about 3 years ago
I use the app WebCatalog to create a YouTube Music web app. Source: about 3 years ago
Im looking for something like WebCatalog that turns websites into 'apps' while still being isolated from one another. Source: about 3 years ago
I just started using this app, and Iโm a pretty big fan: https://webcatalog.io/en/. Source: over 3 years ago
Iโm using Webcatalog to create apps for sites like Disney, Netflix, etc. https://webcatalog.io/en/. Source: over 3 years ago
Fluid - Turn Your Favorite Web Apps into Real Mac Apps.
Apple Machine Learning Journal - A blog written by Apple engineers
Nativeifier - Turn any webpage into a native app
Comet.ml - Comet lets you track code, experiments, and results on ML projects. Itโs fast, simple, and free for open source projects.
Rambox - Digital workspace organizer that allows you to unify as many applications as you want, all in one place. It is perfect for those who care about productivity while working with many business and personal apps.
ML Showcase - A curated collection of machine learning projects