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, Elixir seems to be a lot more popular than Nanonets. While we know about 74 links to Elixir, 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 2 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 2 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: almost 2 years ago
Here is another company, which I just came across by accident, which do the same: https://nanonets.com/. Source: about 2 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 2 years ago
If you've been using asdf to manage and maintain multiple versions of Erlang and Elixir, then vfox is also a good choice for you. - Source: dev.to / 6 days ago
I’m on MacOS and erlang.org, elixir-lang.org, and postgresql.org all suggest installation via Homebrew, which is a very popular package manager for MacOS. - Source: dev.to / about 2 months ago
But regardless of their reasons, they'll note that the service is easily meeting its SLOs. It was written in a highly performant, if idiosyncratic language, and uses patterns which give it a high level of resilience and the ability to recover from many situations automatically. The service is steady as a rock, and left to its own devices will more or less chug along indefinitely once deployed. - Source: dev.to / about 2 months ago
As you might have guessed, one of the main use cases for entr is to rerun tests whenever files change. I'm an Elixir engineer, and I use entr to run mix test continuously whenever I save an Elixir file. - Source: dev.to / 6 months ago
The diagram demonstrates the communication pathway between the browser and the Postgres database through the Electric service. Essentially, Electric Sync Service, an Elixir application, orchestrates active-active data replication between the user's local DB and Postgres. - Source: dev.to / 6 months ago
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