Apple Core ML
Amazon Machine Learning
TensorFlow Lite
Roboflow Universe
ML5.js
Machine Learning Playground
Lobe
Apple Machine Learning Journal
Algorithmia
Managed MLflow
neptune.ai
5Analytics
MCenter
Numericcal
ARGONAUT
Datatron
Apple Core ML AlgorithmiaApple Core ML might be a bit more popular than Algorithmia. We know about 7 links to it since March 2021 and only 5 links to Algorithmia. 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 / 2 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: 12 months 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 / 12 months ago
This is the developer documentation where they advertise the APIs - https://developer.apple.com/machine-learning/. Source: over 2 years ago
To push a model into production, there are additional concerns which the tools in the versioning, deployment and release space aim to solve. This includes obtaining adequate infrastructure to run the model reliably and facilitating easy model release or rollback. Solutions in the MLOps space includes Kubeflow, Pachyderm and Algorithmia. - Source: dev.to / over 2 years ago
And for enterprises that want to do the same with ML you can use algorithmia.com. Source: over 2 years ago
Algorithmia advertises themselves as an MLops platform for data scientists, and they provide an easy way to host models on a scalable REST API. Source: over 2 years ago
Seems similar to https://algorithmia.com. Source: over 2 years ago
Algorithmia.com — Host algorithms for free. Includes free monthly allowance for running algorithms. Now with CLI support. - Source: dev.to / almost 3 years ago
Amazon Machine Learning - Machine learning made easy for developers of any skill level
Managed MLflow - Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.
TensorFlow Lite - Low-latency inference of on-device ML models
neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.
Roboflow Universe - You no longer need to collect and label images or train a ML model to add computer vision to your project.
5Analytics - The 5Analytics AI platform enables you to use artificial intelligence to automate important commercial decisions and implement digital business models.
