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StackML VS Apple Machine Learning Journal

Compare StackML VS Apple Machine Learning Journal and see what are their differences

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StackML logo StackML

Machine Learning platform in-browser, for creators

Apple Machine Learning Journal logo Apple Machine Learning Journal

A blog written by Apple engineers
  • StackML Landing page
    Landing page //
    2021-10-02
  • Apple Machine Learning Journal Landing page
    Landing page //
    2022-12-13

Category Popularity

0-100% (relative to StackML and Apple Machine Learning Journal)

StackML

Apple Machine Learning Journal

AI
23 23%
AI
77% 77
Developer Tools
23 23%
Developer Tools
77% 77
Data Science And Machine Learning
21 21%
Data Science And Machine Learning
79% 79
Education
100 100%
Education
0% 0

User comments

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Social recommendations and mentions

Based on our record, Apple Machine Learning Journal seems to be more popular. 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.

StackML mentions (0)

We have not tracked any mentions of StackML yet. Tracking of StackML recommendations started around Mar 2021.

Apple Machine Learning Journal mentions (6)

  • Does anyone else suspect that the official iOS ChatGPT app might be conducting some local inference / edge-computing? [Discussion]
    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: 11 months ago
  • Which papers should I implement or which Projects should I do to get an entry level job as a Computer vision engineer at MAANG ?
    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
  • Apple’s secrecy created engineer burnout
    They have something for ML: https://machinelearning.apple.com. - Source: Hacker News / almost 2 years ago
  • [D] Is anyone working on open-sourcing Dall-E 2?
    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
  • How does Apple achieve both secrecy and quality for a release?
    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
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What are some alternatives?

When comparing StackML and Apple Machine Learning Journal, you can also consider the following products

Amazon Machine Learning - Machine learning made easy for developers of any skill level

Alcamy - Free, open self-learning platform. Learn & teach anything.

Machine Learning Playground - Breathtaking visuals for learning ML techniques.

Lobe - Visual tool for building custom deep learning models

ZILLIN - Create large accurate training data sets fast

ML5.js - Friendly machine learning for the web

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