Propel vs AutoGluon: What are the differences?

What is Propel? Machine learning for JavaScript. Propel provides a GPU-backed numpy-like infrastructure for scientific computing in JavaScript.

What is AutoGluon? *AutoML Toolkit for Deep Learning *. It automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy deep learning models on image, text, and tabular data.

Propel and AutoGluon can be categorized as "Machine Learning" tools.

Some of the features offered by Propel are:

• Run anywhere, in the browser or natively from Node
• Target multiple GPUs and make TCP connections
• PhD optional

On the other hand, AutoGluon provides the following key features:

• Quickly prototype deep learning solutions for your data with few lines of code
• Leverage automatic hyperparameter tuning, model selection / architecture search, and data processing
• Automatically utilize state-of-the-art deep learning techniques without expert knowledge

Propel and AutoGluon are both open source tools. Propel with 2.79K GitHub stars and 80 forks on GitHub appears to be more popular than AutoGluon with 1.72K GitHub stars and 193 GitHub forks.