Preparing Training Data and Models
Explore how to prepare data for training and build a simple linear regression model using Gradio. Understand one-hot encoding for categorical data and evaluate model performance. This lesson helps you create an interactive UI to deploy and test your machine learning model for predicting sale listing prices.
Building a modeling pipeline in Gradio
In this chapter, we will build a fully functioning machine learning pipeline in Gradio. We will learn how to prepare data for training, train a basic machine learning model, and create a UI allowing users to infer values from the trained model. This is one of the core use cases of Gradio: to allow models to be quickly deployed and tested by the users.
Example background: Predicting sale listing prices
In this chapter, we will build a model to predict sale listing prices. In the dataset, we have property attributes for each sale listing. Our goals will be to:
Prepare training data so that it is ready to be used for modeling.
Train a linear ...