This project aims to visualize and provide various insights from a dataset of Indian automobiles by performing data analysis using machine learning algorithms in the R programming language. The dataset includes information on various features of Indian cars, such as model, manufacturer, year, transmission, engine, and power.
- Feature Prediction: Estimate the price of specific car models using other attributes in the dataset by applying machine learning algorithms like Linear Regression.
- Correlation Analysis: Study the relationship between different attributes of the Indian automobile dataset. This involves:
- 📊 Statistically analyzing the correlation between attributes.
- 📈 Visualizing these correlations to draw meaningful insights.
- Prediction Model: Develop a prediction model that can accurately predict the price of a vehicle based on its other attributes.
- Consumer Insights: Provide consumers with accurate price predictions, helping them avoid underestimations that could lead to loss of automobile value.
- Industry Use Case: Create a practical tool for the industry to offer valuable insights into the various attributes of automobiles. This can guide both market analysis and the development of successful automobile products.
- Data Collection: Gather a comprehensive dataset of Indian cars, including features such as model, manufacturer, year, transmission type, engine specifications, and power ratings.
- Data Storage: Store and manage the dataset using Hadoop Distributed File System (HDFS) to handle large volumes of data efficiently.
- Data Analysis: Use statistical methods to analyze the correlation between different attributes of the cars.
- Machine Learning: Apply Linear Regression and other machine learning algorithms to build a model capable of predicting car prices based on other features.
- Visualization: Create visual representations of the data to make the findings easily understandable and actionable.
- Programming Language: R
- Data Storage: Hadoop Distributed File System (HDFS)
- Machine Learning Algorithms: Linear Regression
- Data Visualization: R's visualization libraries
- A predictive model for car prices based on various attributes.
- Insights into the relationships between different car features.
- Enhanced understanding of the factors influencing automobile prices in the Indian market.
- Practical applications for consumers and the automobile industry to make informed decisions.
This project will provide valuable insights into the Indian automobile market by leveraging data analysis and machine learning techniques. By accurately predicting car prices and understanding the correlations between different attributes, this analysis will support better decision-making for both consumers and industry stakeholders.