Car Sense Analytics

Overview

This project is focused on exploring and analyzing a dataset of cars to uncover insights using advanced machine learning algorithms. The primary objective is to apply algorithms like Stochastic Gradient Descent (SGD) and neural networks to predict the segments and class of cars

Project Objectives

1. Data Exploration: Perform an initial analysis of the car dataset to understand its structure, identify key features, and detect any anomalies or missing values.
2. Feature Engineering: Enhance the dataset by creating new features, normalizing data, and preparing it for machine learning models.
3. Model Development: Implement various machine learning algorithms, including Stochastic Gradient Descent (SGD) and neural networks, to predict car segments and class.
4. Model Evaluation: Evaluate the performance of the models using appropriate metrics, perform hyperparameter tuning, and compare the effectiveness of different algorithms.
5. Insights & Visualization: Visualize the results of the analysis to highlight key insights and trends in the car data.

Kaggle

• Dataset.

• Notebook.