AutoGluon vs Chainer

Chainer vs AutoGluon: What are the differences?

What is Chainer? A Powerful, Flexible, and Intuitive Framework for Neural Networks. It is an open source deep learning framework written purely in Python on top of Numpy and CuPy Python libraries aiming at flexibility. It supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort.

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.

Chainer and AutoGluon can be primarily classified as "Machine Learning" tools.

Some of the features offered by Chainer are:

• Supports CUDA computation
• Runs on multiple GPUs
• Supports various network architectures

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

Chainer and AutoGluon are both open source tools. It seems that Chainer with 5.25K GitHub stars and 1.37K forks on GitHub has more adoption than AutoGluon with 1.72K GitHub stars and 193 GitHub forks.