Tabular Classification
Scikit-learn
English
regression
classification
salary-prediction
stack-overflow
gradient-boosting
random-forest
logistic-regression
clustering
feature-engineering
tabular
Instructions to use rotemvahava/stackoverflow-salary-predictor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use rotemvahava/stackoverflow-salary-predictor with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("rotemvahava/stackoverflow-salary-predictor", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -108,6 +108,8 @@ I plotted median salary by age group to see whether earnings keep growing or pla
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I compared total years of coding (including hobby) against years of professional coding to see if early starters earn more later.
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**Finding:** Professional years matter much more than total years. A developer who started coding as a teenager but has 5 years of professional experience earns roughly the same as someone who started coding professionally at age 30 with 5 years of experience. The "hobby head start" doesn't translate into a measurable salary advantage at the same level of professional tenure.
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I compared total years of coding (including hobby) against years of professional coding to see if early starters earn more later.
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**Finding:** Professional years matter much more than total years. A developer who started coding as a teenager but has 5 years of professional experience earns roughly the same as someone who started coding professionally at age 30 with 5 years of experience. The "hobby head start" doesn't translate into a measurable salary advantage at the same level of professional tenure.
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