No features have been listed yet.
No Doczilla videos yet. You could help us improve this page by suggesting one.
Doczilla's answer
At Doczilla, we embarked on a mission driven by necessity. Faced with the challenge of converting HTML into polished documents and images, we scoured the landscape for a solution that aligned perfectly with our needs. Surprisingly, we found none that matched our specific use case.
Our platform is our response to this gap. We've designed a fully managed API dedicated to simplifying the creation of PDFs and screenshots.
Well written docs, easy to use.
Based on our record, Apple Core ML seems to be more popular. It has been mentiond 7 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.
On the machine learning side of AI, they have CoreML. You can drag-and-drop images into Xcode to train an image classifier. And run the models on device, so if solar flares destroy the cell phone network and terrorists bomb all the data centers, your phone could still tell you if it's a hot dog or not. https://developer.apple.com/machine-learning/ https://developer.apple.com/machine-learning/core-ml/... - Source: Hacker News / 3 months ago
Apple has actually created ML chipsets, so AI can be executed natively, on-device. https://developer.apple.com/machine-learning/. - Source: Hacker News / 4 months ago
For your reference, Apple's pages for Machine Learning for Developers and for their research. The Apple Neural Engine was custom designed to work better with their proprietary machine learning programs -- and they've been opening up access to developers by extending support / compatibility for TensorFlow and PyTorch. They've also got CoreML, CreateML, and various APIs they are making to allow more use of their... Source: about 1 year ago
> It’d be one thing if Apple actually worked on AI softwares a bit and made it readily available to developers. * Apple Silicon CPUs have a Neural Engine specifically made for fast ML-inference * Apple supports PyTorch (https://developer.apple.com/metal/pytorch/) * Apple has its own easily accessible machine-learning framework called Core-ML (https://developer.apple.com/machine-learning/) So it would be inaccurate... - Source: Hacker News / about 1 year ago
This is the developer documentation where they advertise the APIs - https://developer.apple.com/machine-learning/. Source: over 2 years ago
Doppio.sh - From HTML to PDF or PNG with the world leading rendering technology
Amazon Machine Learning - Machine learning made easy for developers of any skill level
pdflayer - Free, powerful HTML to PDF API supporting both URL and raw HTML conversion. Unlimited document size, lightning-fast and compatible PHP, Python, Ruby, etc.
TensorFlow Lite - Low-latency inference of on-device ML models
DocRaptor - As the only API powered by the Prince HTML-to-PDF engine, DocRaptor provides the best support for complex PDFs with powerful support for headers, page breaks, page numbers, flexbox, watermarks, accessible PDFs, and much more
Roboflow Universe - You no longer need to collect and label images or train a ML model to add computer vision to your project.