Google AutoML Tables vs Yellowbrick

Google AutoML Tables vs Yellowbrick: What are the differences?

What is 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.

What is Yellowbrick? Visual analysis and diagnostic tools to facilitate machine learning model selection. It is a suite of visual diagnostic tools called "Visualizers" that extend the scikit-learn API to allow human steering of the model selection process. In a nutshell, it combines scikit-learn with matplotlib in the best tradition of the scikit-learn documentation, but to produce visualizations for your machine learning workflow.

Google AutoML Tables and Yellowbrick belong to "Machine Learning Tools" category of the tech stack.

Some of the features offered by Google AutoML Tables are:

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

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

• Evaluate the stability and predictive value of machine learning models and improve the speed of the experimental workflow
• Provide visual tools for monitoring model performance in real-world applications
• Provide visual interpretation of the behavior of the model in high dimensional feature space.