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Apple Machine Learning Journal VS Managed MLflow

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

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Apple Machine Learning Journal logo Apple Machine Learning Journal

A blog written by Apple engineers

Managed MLflow logo Managed MLflow

Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.
  • Apple Machine Learning Journal Landing page
    Landing page //
    2022-12-13
  • Managed MLflow Landing page
    Landing page //
    2023-05-15

Category Popularity

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

Apple Machine Learning Journal

Managed MLflow

AI
100 100%
AI
0% 0
Data Science And Machine Learning
40 40%
Data Science And Machine Learning
60% 60
Developer Tools
100 100%
Developer Tools
0% 0
Data Science Notebooks
0 0%
Data Science Notebooks
100% 100

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.

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: 12 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
View more

Managed MLflow mentions (0)

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

What are some alternatives?

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

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

Algorithmia - Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.

Machine Learning Playground - Breathtaking visuals for learning ML techniques.

neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.

Lobe - Visual tool for building custom deep learning models

Iterative.ai - Iterative removes friction from managing datasets and ML models and introduces seamless data scientists collaboration.

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