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You could say a lot of things about AWS, but among the cloud platforms (and I've used quite a few) AWS takes the cake. It is logically structured, you can get through its documentation relatively easily, you have a great variety of tools and services to choose from [from AWS itself and from third-party developers in their marketplace]. There is a learning curve, there is quite a lot of it, but it is still way easier than some other platforms. I've used and abused AWS and EC2 specifically and for me it is the best.
Based on our record, Amazon AWS seems to be a lot more popular than Apple Machine Learning Journal. While we know about 381 links to Amazon AWS, we've tracked only 6 mentions of Apple Machine Learning Journal. 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.
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
Additionally, explore AWS, DigitalOcean, Azure, and IBM Cloud for more options. - Source: dev.to / about 21 hours ago
AWS (Amazon Web Services) is a comprehensive cloud computing platform provided by Amazon, offering a wide range of services including computing power, storage, and databases. It enables businesses and developers to access and use scalable and cost-effective cloud resources on-demand. - Source: dev.to / 2 days ago
Amazon Web Services (AWS) is one of the most popular cloud computing platforms worldwide. It offers a comprehensive suite of services that enable developers and businesses to build, deploy, and scale applications with ease. - Source: dev.to / 3 days ago
Before installing Quickwit, you'll need to create an object storage bucket to hold your Quickwit indexes. You can use use your choice of Cloud provider such as Scaleway, AWS S3 or MinIO. Refer to our official Quickwit documentation for storage configuration details. - Source: dev.to / 5 days ago
Having an AWS Account: Sign up for an AWS account at AWS if you don't already have one. This will be necessary for deploying your application to Amazon EC2. - Source: dev.to / 4 days ago
Amazon Machine Learning - Machine learning made easy for developers of any skill level
DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.
Machine Learning Playground - Breathtaking visuals for learning ML techniques.
Microsoft Azure - Windows Azure and SQL Azure enable you to build, host and scale applications in Microsoft datacenters.
Lobe - Visual tool for building custom deep learning models
Linode - We make it simple to develop, deploy, and scale cloud infrastructure at the best price-to-performance ratio in the market.Sign up to Linode through SaaSHub and get a $100 in credit!