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
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Based on our record, Ruby on Rails seems to be a lot more popular than Nanonets. While we know about 142 links to Ruby on Rails, we've tracked only 6 mentions of Nanonets. 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
Ruby on Rails open source projects. Contribute and learn at the same time. - Source: dev.to / 12 days ago
Speed of Development: Frameworks such as Django or Rails accelerate the development process. - Source: dev.to / 13 days ago
This ecosystem is fueled by repositories hosting powerful languages, functions, and versatile tools—from backend frameworks like Django and Ruby on Rails to containerization with Docker and distributed version control via Git. Moreover, indie hackers can also utilize open source design tools (e.g. GIMP, Inkscape) and analytics platforms such as Matomo. - Source: dev.to / 14 days ago
Ruby on Rails (RoR) is one of the most renowned web frameworks. When combined with SQL databases, RoR transforms into a powerhouse for developing back-end (or even full-stack) applications. It resolves numerous issues out of the box, sometimes without developers even realizing it. For example, with the right callbacks, complex business logic for a single API action is automatically wrapped within a transaction,... - Source: dev.to / 24 days ago
As it's just you I'd stick with Ruby on Rails 8[1] as you already know it and I think it could realistically easily achieve what you're proposing. There's lots of libraries to for calling out external AI services. e.g. Something like FastMCP[2] From the sound of it that's all you need. I'd use Hotwire[3] for the frontend and Hotwire Native if you want to rollout an app version quickly. I'd back it with... - Source: Hacker News / about 2 months ago
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