No Apple Machine Learning Journal videos yet. You could help us improve this page by suggesting one.
Based on our record, Papers We Love should be more popular than Apple Machine Learning Journal. It has been mentiond 9 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.
Papers We Love (PWL) is a community built around reading, discussing and learning more about academic computer science papers. This repository serves as a directory of some of the best papers the community can find, bringing together documents scattered across the web. You can also visit the Papers We Love site for more info. - Source: dev.to / 6 months ago
You might be interested in https://paperswelove.org. Source: about 1 year ago
Public Service Announcement. Reading research papers is so important for your growth and career, please put in a process to do it at least once in a month or two. (I will try to write a blog post about why it is important, and how to go about it, since I see there is a big need for this.) Papers We Love is a great resource, https://paperswelove.org/, if you like to get involved in a community to dip your feet into... - Source: Hacker News / about 1 year ago
Want to make sure you’re aware of https://paperswelove.org/. Source: about 1 year ago
It’s not a subreddit, but check out https://paperswelove.org/. My local group is great. 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
Academus - Read research papers as interactive webpages
Amazon Machine Learning - Machine learning made easy for developers of any skill level
Arxiv Vanity - Read academic papers from arXiv as responsive web pages
Machine Learning Playground - Breathtaking visuals for learning ML techniques.
Startup Emails - Responsive HTML email templates for startups
Lobe - Visual tool for building custom deep learning models