Uploadcare is file management platform and a CDN for user-generated content. It is a robust file API for uploading, managing, processing, rendering, optimizing and delivering users’ content.
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Uploadcare's answer
Uploadcare's answer
While Uploadcare products have been disrupting the traditional content delivery market since 2011, the company has now become a reliable technologicalpartner in marketplaces, e-commerce, e-learning, SaaS, and healthcare industries.
Uploadcare's answer
The platform fits the developers' needs, from building passion projects and simple websites to large-scale applications managing tons of digital media.
Based on our record, Uploadcare should be more popular than Neuro. It has been mentiond 9 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.
Feel free to learn more about Uploadcare, and explore other tutorials, such us how to upload files with React or Angular, or considering what kind of magic you can do with the uploaded images following our extracting colors guide 🎨. - Source: dev.to / 11 months ago
Sign up for an Uploadcare account: Go to the Uploadcare website and sign up for an account. You will need to provide your email address and create a password. - Source: dev.to / over 1 year ago
Only answer: Https://uploadcare.com/. Source: almost 2 years ago
Side note, https://uploadcare.com/ looks pretty reasonably priced? Source: about 2 years ago
Some good file storage for web, like this: https://uploadcare.com/. Source: about 2 years ago
Projects are definitely the best way to learn models. Build things for fun that do things in topics/fields that you care about or think is cool. a few years ago when I was getting into ML stuff I build fantasy football things that weren't even useful but provided an actual use case. Then I did more complicated stuff with photography and lighting because I did real estate photography. As far as ML libraries go,... Source: almost 3 years ago
So far I’ve seen AWS Sagemaker kind of allows for a situation like this, but would rather not deal with all that config. Algorithmia and Nuclio are too enterprise focused. Neuro is new and looks great, but from my understanding I would still need to create a lambda instance myself that then calls neuro’s servers - too indirect. Is there a total solution out there for this? Source: about 3 years ago
A couple of weeks ago I put out a post on DeepSpeech running on the serverless setup at Neuro (https://getneuro.ai), and I've now got Silero running there as well. I've found this model is a lot faster than DS and way more accurate. Seeing around 300ms per request at the moment, hopefully will be closer to 100ms soon but this is a pretty decent speed in this application already. Source: over 3 years ago
I just made a streaming script connecting Deepspeech to serverless GPUs at Neuro (https://getneuro.ai). Was a fun piece of work, and cool to play around with. You can find the source here: https://github.com/neuro-ai-dev/npu_examples/tree/main/deepspeech. Source: over 3 years ago
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