The price of a car depends on a lot of factors like the goodwill of the brand of the car, features of the car, horsepower and the mileage it gives and many more. Car price prediction is one of the major research areas in machine learning. In this project, I am going to Apply Data science techniques to Undertand the core features of the data and build a Machine Learning and deep learning models to predict the car sale price.
Projrct content and sections
- Business problem Identification
-
- Explorative Data analytics
-
- Data preparation & Cleaning
-
- Data Visualization
-
- Data Understanding and Interprining
-
- Feature selection & Feature Enginering
-
- Understand the Features
-
- Select core Features
-
- Handling Imbalance Data
-
- Encode the catagorical data
-
- Sacle down the data (Apply one hot encoding)
-
- Build MAchine learning models - Split The data
-
- Build the model
-
- Evaluvate the ML model accuracy (1st round)
-
- hyperparameter tuning
-
- Evaluate the ML model accuracy (2st round)
-
- Build Deep Learning Model
-
- Evaluate the DL model accuracy