I’m a Data Science Specialist with a passion for education, sports and life-long learning. You can learn more about me and view my featured work on my website, nicolebid.github.io, or check out the summary table below for insight into projects I've done.
- Languages: Python, R
- Databases: MongoDB, MySQL, PostgreSQL
- Data Analysis: Pandas, GeoPandas, NumPy, Tidyr, Dplyr
- Data Visualization: Altair, Matplotlib, Dash, ggplot2, Shiny
- Machine Learning: Supervised Learning, Unsupervised Learning, Classification, Regression, Time Series Analysis, Clustering, Feature Selection and Engineering, Dimensionality Reduction
- Statistics: Bayesian and Frequentist Methodologies, Hypothesis Testing, A/B Testing, Causal Inference, Regression Analysis
- Other Tools: Git, GitHub Actions, Jupyter Notebook, VSCode, RStudio, Docker, AWS
If you have any questions or ideas for collaboration, I’d love to connect! Feel free to reach out via Linkedin or my contact form on my website.
This table showcases my key projects, along with articles I've written, within data science and education. It outlines the focus area and main technologies utilized.
| Project | Description | Focus Area | Main Tools/Libraries | Completion Date (YYYY-MM) |
Link |
|---|---|---|---|---|---|
| Airbnb Analysis | A machine learning project predicting listing prices based on property features, offering insights into the key factors that drive Airbnb pricing trends. | Machine Learning, Regression Analysis, EDA, Feature Engineering, Model Interpretability | Python, NumPy, pandas, Altair, scikit-learn, SHAP, XGBoost, LightGBM, joblib | 2024-09 | Repo Report |
| Leveraging the Power of AI in Education: Insider Perspectives and Practices | An article discussing educator perspectives on AI in education, containing my insights paired with survey-based results of effective implementations and concerns. | AI in Education | N/A | 2024-08 | Medium Article |
| PWHL Goalie Tracker | A fan-friendly dashboard showcasing goalie statistics and team rankings for the inaugural season of the Professional Women’s Hockey League (PWHL). | Data Visualization | R, Shiny, ggplot2, dplyr | 2024-07 | Repo App |
| Solar Savers: Solar Panel Cost-Effectiveness | A dashboard application designed to assist Canadian homeowners in making informed solar panel purchasing decisions. | Data Visualization | Python, Dash, pandas, GeoPandas, Altair | 2024-04 | Repo App |
| eda_mds | A Python package that kick-starts the EDA stage of machine learning projects, enhancing pandas' EDA functions with four functions that deliver insights and identify potential problems in the dataset. | Python Package Development, EDA | Python, pandas, GitHub Actions | 2024-02 | Repo Vingette |
| Red Wine Quality Prediction | This project aimed to create a classification model to predict red wine quality based on its physiochemical properties. The best model showed reasonable accuracy, highlighting areas for improvement in handling outliers. | Machine Learning, Classification, Unit Testing | GitHub Actions, Docker, Python, pandas, scikit-learn, matplotlib, pickle, seaborn, NumPy, Altair | 2023-12 | Repo Report |
| Gentrification in Vancouver: Teaching Mathematics through a Social Justice Lens | An article discussing the implementation and difficulties of teaching mathematics alongside social justice with example lesson activities. | Mathematics Education & Social Justice | N/A | 2017-03 | Article (pg. 13-15) |