DeepSpeed vs Google AutoML Tables

DeepSpeed vs Google AutoML Tables: What are the differences?

DeepSpeed: A deep learning optimization library that makes distributed training easy, efficient, and effective (By Microsoft). It is a deep learning optimization library that makes distributed training easy, efficient, and effective. It can train DL models with over a hundred billion parameters on the current generation of GPU clusters while achieving over 5x in system performance compared to the state-of-art. Early adopters of DeepSpeed have already produced a language model (LM) with over 17B parameters called Turing-NLG, establishing a new SOTA in the LM category; Google AutoML Tables: Automatically build and deploy machine learning models on structured data. Enables your entire team of data scientists, analysts, and developers to automatically build and deploy machine learning models on structured data at massively increased speed and scale.

DeepSpeed and Google AutoML Tables can be categorized as "Machine Learning" tools.

Some of the features offered by DeepSpeed are:

• Distributed Training with Mixed Precision
• Model Parallelism
• Memory and Bandwidth Optimizations

On the other hand, Google AutoML Tables provides the following key features:

• Increases model quality
• Easy to build models
• Easy to deploy

DeepSpeed is an open source tool with 1.98K GitHub stars and 134 GitHub forks. Here's a link to DeepSpeed's open source repository on GitHub.