NanoNets is a Deep Learning web platform that makes it easier than ever before to use Deep Learning in practical applications. It combines the convenience of a web-based platform with Deep Learning models to create image recognition and object classification applications for your business. You can easily build and integrate deep learning models using NanoNets’ API. You can also work with our pre-trained models which have been trained on huge datasets and return accurate results. NanoNets has leveraged recent advances in Deep Learning to build rich representations of data which are transferable across tasks. It’s as simple as uploading your input, generating the output and getting a functioning and highly accurate Deep Learning model for your AI needs. NanoNets is revolutionary because it allows you to train models without large datasets. With just 100 images you can train a model on our platform to detect features and classify images with a high degree of accuracy. NanoNets benefits you in four important ways: ● It reduces the amount of data needed to build a Deep Learning Model ● NanoNets handles the infrastructure for hosting and training the model, and for the run time ● It reduces the cost of running deep learning models by sharing infrastructure across models ● It is possible for anyone to build a deep learning model
Based on our record, Backbone.js should be more popular than Nanonets. It has been mentiond 17 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.
Want to automate repetitive manual tasks? Check our Nanonets workflow-based document processing software. Source: almost 3 years ago
Nanonets is a no-code, workflow-based, and AI-enhanced intelligent document processing platform. It automates all document processes and is built on a robust, intelligent, self-learning OCR API that allows users to extract required data from documents in minutes. Source: almost 3 years ago
Check out our website here https://nanonets.com/ for more. We also have some free tools where you can experience our product for free (like https://nanonets.com/online-ocr). Source: about 3 years ago
Here is another company, which I just came across by accident, which do the same: https://nanonets.com/. Source: about 3 years ago
We will be using Python3.6+, Django web framework, Nanonets for character extraction from an image, Cloudinary for image storage and Google Search API for performing the searches. - Source: dev.to / over 3 years ago
Https://backbonejs.org/#View There is also a github repo that has examples of MVC patterns adapted to the web platform. - Source: Hacker News / about 1 month ago
Underscore was created by Jeremy Ashkenas (the creator of Backbone.js) in 2009 to provide a set of utility functions that JavaScript lacked at the time. It was also created to work with Backbone.js, but it slowly became a favorite among developers who needed utility functions that they could just call and get stuff done with without having to worry about the inner implementations and browser compatibility. - Source: dev.to / 5 months ago
Got it thanks for the context. I've read the web app and it seems to me it is just https://backbonejs.org/ re-written in Typescript and allows JSX. I'm very certain Typescript and JSX will have improved the DX for Backbone like apps, but it doesn't address all of the other issues that teams had with Backbone. e.g. Cyclical event propagation, state stored in the DOM (i.e. Appendchild is error prone in large code... - Source: Hacker News / almost 2 years ago
Even further nowadays, docs are created using Docusaurus. I don't have problem with it but documentation should be good (eye) friendly than easy to write. Why not be creative while writing docs such as - Backbone.js - https://backbonejs.org Or https://backbonejs.org/docs/backbone.html as code annotation. - Source: Hacker News / about 2 years ago
What we see, a decade ago, are that many of the "popular" libraries, frameworks, and methods, not surprisingly, have gone by the wayside, a lot that have remained in current code as difficult-to-removemodernize legacy cruft (Bower, Gulp, Grunt, Backbone, Angular 1, ...), and then we have the small minority that are still here. Some that remain have had their utility lessened/questioned by platform and language... - Source: dev.to / over 2 years ago
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