Python Marketing Regression Model
Budget: $30 – $250 USD
I have a clean set of numerical marketing data and I’m ready to kick off a regression-based machine learning project in Python. The goal is to uncover relationships in the data and build a reliable model I can iterate on for future campaigns.
What I need right now is a fully-documented workflow in a Jupyter notebook: data loading, exploratory analysis, feature engineering, model selection, training, validation, and performance reporting. Popular libraries such as pandas, scikit-learn, NumPy, matplotlib or seaborn should be used so I can keep everything in a familiar, open-source stack.
Please structure the work so I can follow every step and adapt it later. Simple, well-named functions, in-line comments, and a brief narrative explaining why each modelling decision was made will help me learn from the code.
Deliverables
• Jupyter notebook (.ipynb) containing the end-to-end regression pipeline
• Any supporting .py modules or utility scripts if you break code out of the notebook
• README with environment setup (Python version, pip/conda requirements) and instructions to reproduce results
If you have hands-on experience with marketing analytics tasks—campaign performance, lifetime value prediction, or media mix modelling—let me know. I’m ready to get started right away.
What I need right now is a fully-documented workflow in a Jupyter notebook: data loading, exploratory analysis, feature engineering, model selection, training, validation, and performance reporting. Popular libraries such as pandas, scikit-learn, NumPy, matplotlib or seaborn should be used so I can keep everything in a familiar, open-source stack.
Please structure the work so I can follow every step and adapt it later. Simple, well-named functions, in-line comments, and a brief narrative explaining why each modelling decision was made will help me learn from the code.
Deliverables
• Jupyter notebook (.ipynb) containing the end-to-end regression pipeline
• Any supporting .py modules or utility scripts if you break code out of the notebook
• README with environment setup (Python version, pip/conda requirements) and instructions to reproduce results
If you have hands-on experience with marketing analytics tasks—campaign performance, lifetime value prediction, or media mix modelling—let me know. I’m ready to get started right away.