Use the Scikit Learn and Keras libraries to build a Linear regression model to predict the price of a house. Understand the steps involved in preparing data and configuring regression models.
Learning Objectives
Linear Regression Models: Building Simple Regression Models with Scikit Learn and Keras
- Course Overview
- use the Pandas library to load a dataset in the form of a CSV file into a Dataframe for consumption by a linear regression model
- create training and validation sets for your regression model
- configure a linear regression model and then train and validate it and view the metrics for the model and visualize it using Matplotlib
- install the Keras library and prepare the dataset for consumption by a Keras model
- define the architecture for a Keras sequential model and initialize it
- compile a Keras sequential model by defining the loss function and optimizer and train it to get the optimal values for weights and biases
- evaluate a Keras sequential model by using it to make predictions on test data
- work with training sets and the Keras sequential model