Software Alternatives, Accelerators & Startups

EduDo VS Apple Core ML

Compare EduDo VS Apple Core ML and see what are their differences

EduDo logo EduDo

EduDo is a video discussion platform

Apple Core ML logo Apple Core ML

Integrate a broad variety of ML model types into your app
  • EduDo Landing page
    Landing page //
    2022-03-20
  • Apple Core ML Landing page
    Landing page //
    2023-06-13

EduDo videos

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Apple Core ML videos

IBM Watson & Apple Core ML Collaboration - What it means for app development

Category Popularity

0-100% (relative to EduDo and Apple Core ML)
Education
100 100%
0% 0
Developer Tools
0 0%
100% 100
Productivity
100 100%
0% 0
AI
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apple Core ML should be more popular than EduDo. It has been mentiond 7 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.

EduDo mentions (1)

  • I'm an ex-VC turned startup founder building a video-based discussions platform and researching network effects
    Startup founder – decided to leave VC and start my own company EduDo. We're building a video-based discussions platform allowing folks to share insights and opinions in an interactive an engaging way. We've already released an MVP, became a Mobile App of the year by Product Hunt, raised $500k, came through a pivot, and now are soft launching the new concept;. Source: over 2 years ago

Apple Core ML mentions (7)

  • Ask HN: Where is Apple? They seem to be left out of the AI race?
    On the machine learning side of AI, they have CoreML. You can drag-and-drop images into Xcode to train an image classifier. And run the models on device, so if solar flares destroy the cell phone network and terrorists bomb all the data centers, your phone could still tell you if it's a hot dog or not. https://developer.apple.com/machine-learning/ https://developer.apple.com/machine-learning/core-ml/... - Source: Hacker News / 3 months ago
  • The Magnitude of the AI Bubble
    Apple has actually created ML chipsets, so AI can be executed natively, on-device. https://developer.apple.com/machine-learning/. - Source: Hacker News / 5 months ago
  • 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: about 1 year ago
  • Apple to occupy 90% of TSMC 3nm capacity in 2023
    > It’d be one thing if Apple actually worked on AI softwares a bit and made it readily available to developers. * Apple Silicon CPUs have a Neural Engine specifically made for fast ML-inference * Apple supports PyTorch (https://developer.apple.com/metal/pytorch/) * Apple has its own easily accessible machine-learning framework called Core-ML (https://developer.apple.com/machine-learning/) So it would be inaccurate... - Source: Hacker News / about 1 year ago
  • The iPhone 13 is a pitch-perfect iPhone 12S
    This is the developer documentation where they advertise the APIs - https://developer.apple.com/machine-learning/. Source: almost 3 years ago
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What are some alternatives?

When comparing EduDo and Apple Core ML, you can also consider the following products

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

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

TeenUp - A learning platform designed for teens by teens

TensorFlow Lite - Low-latency inference of on-device ML models

PalPark - Curate and share your learnings by topics

Roboflow Universe - You no longer need to collect and label images or train a ML model to add computer vision to your project.