Google CLOUD AUTOML
Qubole
BigML
TensorFlow
Scikit-learn
machine-learning in Python
AWS SageMaker Ground Truth
RapidMiner
Apple Machine Learning Journal
Amazon Machine Learning
Machine Learning Playground
Lobe
ML5.js
A.I. Experiments by Google
mlblocks
Know Your Data
Google CLOUD AUTOMLApple Machine Learning Journal might be a bit more popular than Google CLOUD AUTOML. We know about 6 links to it since March 2021 and only 6 links to Google CLOUD AUTOML. 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.
There are several no-code AI websites that you can use like Amazon SageMaker, Apple CreateML or Google AutoML. Source: about 1 year ago
GCP, on the other hand, offers two top options: Google Cloud AutoML, for beginners, and Google Cloud Machine Learning Engine, for handling tasking projects. GCP also provides Tenserflow and Vertex AI complicated machine learning abilities. - Source: dev.to / over 1 year ago
Just outsource the work to Google or Amazon. Source: over 2 years ago
We can also note the appearance of Machine Learning, creating dynamic processes over data that would have been tedious to analyse, either by hand or through specific code. This enables writing potentially complex behaviours with a few lines of code in some cases. Even then, there is some automation of it to the point where you only have to provide data to get working results. - Source: dev.to / almost 3 years ago
You might want to check out automl Google AutoML. Source: almost 3 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
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
Amazon Machine Learning - Machine learning made easy for developers of any skill level
BigML - BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.
Machine Learning Playground - Breathtaking visuals for learning ML techniques.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Lobe - Visual tool for building custom deep learning models