Learn how to use the Scikit Learn and Keras libraries to build a linear regression model to predict a house price. This course reviews the steps needed to prepare data and configure regression models. It shows how to prepare a data set to feed a linear regression model; how to use the Pandas library to load a CSV data set file; and how to configure, train, and validate linear regression models. The course also shows how to visualize metrics with Matplotlib; how to prepare data for a Keras model, how to learn the architecture for a Keras sequential model and initialize it; and finally, how train it to use optimal weights and biases for machine learning solutions.
Learning Objectives
Learn how to use the Scikit Learn and Keras libraries to build a linear regression model to predict a house price. This course reviews the steps needed to prepare data and configure regression models. It shows how to prepare a data set to feed a linear regression model; how to use the Pandas library to load a CSV data set file; and how to configure, train, and validate linear regression models. The course also shows how to visualize metrics with Matplotlib; how to prepare data for a Keras model, how to learn the architecture for a Keras sequential model and initialize it; and finally, how train it to use optimal weights and biases for machine learning solutions.