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, yt-dlp seems to be a lot more popular than Nanonets. While we know about 870 links to yt-dlp, 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: about 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: about 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: about 2 years ago
Here is another company, which I just came across by accident, which do the same: https://nanonets.com/. Source: over 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 / almost 3 years ago
Update I got this: "I would recommend watching the video in FreeTube, writing down all the time ranges and then using yt-dlp with it's --download-sections option. https://github.com/yt-dlp/yt-dlp". - Source: Hacker News / 27 days ago
> Any links or ideas of how to make sure Google is aware of this? Cancel the account. That's the only real signal you can send. Switch to simply downloading YT content: https://github.com/yt-dlp/yt-dlp. - Source: Hacker News / 28 days ago
If you're looking to download source material from the internet, yt-dlp is a great tool that can extract and save videos locally from a wide variety of sources like youtube, twitter and more. - Source: dev.to / about 1 month ago
The classic yt-dlp was how this all began, to be honest this one still confuses me but well figure that out in development. - Source: dev.to / about 2 months ago
This seems to be a pretty straightforward GUI wrapper around https://github.com/Tyrrrz/YoutubeExplode (see https://github.com/PackJC/YoutubeToMP3/blob/main/Form1.cs is a well-maintained public domain alternative. - Source: Hacker News / about 2 months ago
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