This repository contains a Jupyter notebook for a regression case study using the Red Wine Dataset. The study focuses on building regression models to predict the quality of red wine based on various physicochemical properties. It involves data exploration, preprocessing, model building, and evaluation.
The [Springboard Regression Case Study - the Red Wine Dataset - Tier 3.ipynb](Springboard Regression Case Study - the Red Wine Dataset - Tier 3.ipynb) notebook provides a thorough exploration and analysis of the Red Wine Dataset for a regression case study. The notebook covers these key aspects:
- Introduction: Overview of the dataset and the objectives of the case study.
- Data Exploration: Analyzing the dataset to understand the distribution and relationship of different variables.
- Data Preprocessing: Techniques for preparing the data for modeling, such as handling missing values and normalizing data.
- Model Building: Developing various regression models to predict the quality of red wine.
- Model Evaluation and Selection: Evaluating the performance of different models and selecting the most effective one based on certain metrics.
- Conclusion: Summarizing the findings, discussing the implications, and suggesting future work directions.