Portfolio Details

Deep dive into my Data Science and Machine Learning projects, including predictive modeling, exploratory data analysis, and real-world datasets.

BMW Sales Prediction
BMW Sales Prediction
BMW Sales Prediction
Gallery Image
Gallery Image
Gallery Image
Gallery Image
Python Pandas Scikit-Learn Matplotlib Seaborn
Machine Learning
March 2026
Personal Project

BMW Global Sales Prediction

Developed a predictive model to forecast BMW car sales worldwide. Performed data cleaning, feature engineering, and applied machine learning algorithms to derive actionable insights.

Analyzed historical BMW sales data from 2018–2025, exploring trends, seasonality, and market factors. Built regression and ensemble models to accurately predict monthly car sales and provide business insights.

The dataset included multiple global markets with varying sales patterns. Handling missing values, multicollinearity, and scaling features were major challenges. Ensuring model interpretability and performance was critical.

Implemented a Random Forest Regression model with feature selection and hyperparameter tuning. Visualized trends using Matplotlib and Seaborn. Generated predictions for each region with actionable insights for decision-making.

Key Features

  • Global Sales Prediction
  • Data Cleaning & Preprocessing
  • Feature Engineering
  • Random Forest Regression
  • Data Visualization & Insights
  • Performance Evaluation Metrics