Cloudify
Kubernetes
OpenShift
Morpheus
Heroku
Microsoft Azure
Redis
Rancher
Apple Machine Learning Journal
Amazon Machine Learning
Machine Learning Playground
Lobe
A.I. Experiments by Google
ML5.js
mlblocks
ML Showcase
Cloudify provides infrastructure automation using ‘Environment as a Service’ technology to deploy and continuously manage any cloud, private data center, or Kubernetes service from one central point while leveraging existing toolchains; Terraform, Ansible, and more. Use Cloudify to import existing automation templates and scripts and automatically convert them into certified environments. Manage them using the Cloudify console or export these environments to ServiceNow and enable users to deploy, continuously manage and maintain them as part of approval workflows.
Key Values: - Speed up deployments of your Test/Dev/Production environments. - Manage customers' heterogeneous cloud environments. - Enable Continuous Updates (Day-2) for your Production environments. - A clean API to work on top of all your tools that can easily be used within ServiceNow. - Manage Kubernetes clusters at scale.
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Based on our record, Apple Machine Learning Journal should be more popular than Cloudify. It has been mentiond 6 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.
Cloudify looks interesting if you can stand the price, depends how badly you need the features it offers. Source: about 2 years ago
Cloudify is a platform that automates and manages entire lifecycles of an application or network service. Source: over 2 years 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
We even host annual poster sessions of those PhD intern’s work while at our company, and it’ll give you an idea of the caliber of work. It may not be as great as Nvidia, Stryker, Waymo, or Tesla (which are not part of MAANG but I believe are far more ahead in CV), but it’s worth of considering. Source: about 1 year ago
They have something for ML: https://machinelearning.apple.com. - Source: Hacker News / about 2 years ago
They're more subtle about it, I think. https://machinelearning.apple.com/ Some of the papers are pretty good. I don't disagree with your sentiment in aggregate, though. Source: about 2 years ago
Siri is not where it needs to be because Apple refuses to mine user data to enrich it. They also are very hesitant to allow researchers to publish their breakthroughs which makes recruitment very hard. Although this is changing https://machinelearning.apple.com/. - Source: Hacker News / about 2 years ago
Kubernetes - Kubernetes is an open source orchestration system for Docker containers
Amazon Machine Learning - Machine learning made easy for developers of any skill level
OpenShift - OpenShift gives you all the tools you need to develop, host and scale your apps in the public or private cloud. Get started today.
Machine Learning Playground - Breathtaking visuals for learning ML techniques.
Morpheus - Morpheus is integration software designed to help major cloud infrastructure work in harmony. For example, if a company has assets on both Google's and Amazon's cloud services, Morpheus helps bridge the gap to improve productivity.
Lobe - Visual tool for building custom deep learning models
