No Apple Machine Learning Journal videos yet. You could help us improve this page by suggesting one.
Based on our record, GitHub Codespaces seems to be a lot more popular than Apple Machine Learning Journal. While we know about 143 links to GitHub Codespaces, 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.
Then, we had the rise of the cloud and the arrival of cloud-based IDEs. The first cloud-based IDE was PHPanywhere (eventually becoming CodeAnywhere) in 2009, followed by Cloud9 in 2010 (before AWS bought it in 2016), Glitch (2018), GitPod (2019), GitHub Codespaces (2020), and Google’s Project IDX (2024). - Source: dev.to / 5 days ago
If your team is using a Cloud Development Environment such as GitHub Codespaces, or Dev Containers such as Docker, you can even share the installation of dbaeumer.vscode-eslint with your teammates, via devcontainer.json. - Source: dev.to / about 1 month ago
Https://github.com/features/codespaces Currently, it is probably the most convenient for coding on mobile devices. Source: 6 months ago
I am currently right now viewing Angular Essential Training (paid by my company but I have a personal Pluralsight) and using GitHub Codespaces for $4 a month to host the virtuals created for such coding/learning. Source: 6 months ago
I’m very interested in recent advancements in cloud-hosted development environments. GitHub Codespaces is the option I have the most experience with and the one I use more generally. With cloud-hosted development environments, your local machine becomes more of a thin client that facilitates access to the internet and the development environment. That is a considerable step toward enabling better education in... - Source: dev.to / 6 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
replit - Code, create, andlearn together. Use our free, collaborative, in-browser IDE to code in 50+ languages — without spending a second on setup.
Amazon Machine Learning - Machine learning made easy for developers of any skill level
CloudShell - Cloud Shell is a free admin machine with browser-based command-line access for managing your infrastructure and applications on Google Cloud Platform.
Machine Learning Playground - Breathtaking visuals for learning ML techniques.
StackBlitz - Online VS Code Editor for Angular and React
Lobe - Visual tool for building custom deep learning models