An Machine Learning for prediction of car prices.
Problem Statement:
Using linear regression algorithm and predicting the price of an automobile based on the different variables.
Project Description:
We need to get data. We'll use a sample data set for that.The raw data is completely infused in the workspace. The entries includes model, specifications and price. Preprocessing is done before the analyzing part. The data must be clean so that the model can analyze correctly. For that the rows with empty values are removed. A module is added for that process. Individual measurable properties are called features. Each row is representing an automobile and each column represents the feature of that automobile. The model is build accordingly. Now that the data is ready, constructing a predictive model consists of training and testing. We'll use our data to train the model, and then we'll test the model to see how closely it's able to predict prices. Because we want to predict price, which is a number, we'll use a regression algorithm. For this example, we'll use a linear regression model.
https://gallery.cortanaintelligence.com/Experiment/Automobile-Price-Predictor-7
I've developed this in Azure Machine Learning Classic. Great experience.