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Based on our record, TinEye seems to be a lot more popular than Apple Machine Learning Journal. While we know about 922 links to TinEye, 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.
I have a bit of an image-hoarding obsession and spend a lot of time researching pictures I find online in great depth. This involves using sites like tineye.com, Reddit, and Pinterest to identify the source of an image, then tracking down the history, maker, and theory behind it. It's all hobby-based - mainly focused on art, photography, museum oddities, antiques, and fashion that I like. Basically anything... Source: 7 months ago
Used TinEyeto find other places these images ate shared on. No results yet. Source: 7 months ago
Your post has been removed as it's a repost from the past month or one of the top post of all time. Please avoid re-posting memes. Please check http://karmadecay.com, https://tineye.com , or the Google's "Similar Image" search in the future before posting. All of those miss things, but it's a great start. Also make sure to use the search button and check through this link: www.reddit.com/r/im14andthisisdeep/top... Source: 8 months ago
Reposts from the past three months or from the top posts of all time are not allowed. To check if your submission has already been posted here, use KarmaDecay, TinEye, or Google's "Search by image" feature before posting. Source: 11 months ago
Include your submission source in your post's comments. When linking your source, please post it as a top-level comment (directly on the post itself and not replying to another comment) and include one of the following keywords (not case-sensitive): source, original, or credit. Repeatedly breaking this rule may subject you to a temporary ban. You may use sources such as TinEye and Google Image Search to help you... Source: 12 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
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
Google Images - Google Images is a search service owned by Google that allows users to search the World Wide Web for image content.
Amazon Machine Learning - Machine learning made easy for developers of any skill level
SauceNAO - SauceNAO is a reverse image search engine.
Machine Learning Playground - Breathtaking visuals for learning ML techniques.
Yandex.Images - search for images on the internet, search by image
Lobe - Visual tool for building custom deep learning models