Predicting Developer Salaries
- Guided Project
- 2 hours
- Intermediate
- Python
Practice cleaning real-world survey data, engineering features from multi-select fields, and building a linear regression model to predict developer salaries.
Overview
The 2023 Stack Overflow Developer Survey captured tens of thousands of responses describing skills, experience, location, work preferences, and compensation. Your job is to turn that raw, messy dataset into a linear regression model that predicts yearly salary and reveals the factors behind developer pay.
You'll work through a full data science workflow: auditing and dropping sparse columns, filtering outlier salaries, engineering features from multi-select skill lists, encoding high-cardinality categories, and managing multicollinearity before training and evaluating your model. Along the way, you'll interpret coefficients to separate controllable factors like skills and role from fixed ones like geography.
Build and evaluate a linear regression model on Stack Overflow survey data to predict developer salaries and surface the factors that drive compensation.
What You'll Learn
- ✓ Clean and prepare the Stack Overflow survey, tackling heavy missingness and noisy fields.
- ✓ Engineer features from multi-select skill lists and other semi-structured responses.
- ✓ Encode high-cardinality categories while managing multicollinearity among experience signals.
- ✓ Train and interpret a linear regression model to surface the factors that influence developer pay.
Before You Start
- ✓ Familiarity with pandas
- ✓ Basic machine learning concepts, train/test splitting
- ✓ Handling missing data and outliers in real-world datasets
- ✓ Feature engineering and encoding categorical variables
Project Steps
5 steps
- 1 Explore the raw survey
- 2 Trim to salary respondents and retire low-value columns
- 3 Shape the modeling dataset
- 4 Engineer features and build the salary model
- 5 Next Steps
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