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Achievements

Achievement: QuickdrawAchievement: YOLOAchievement: Pull Sharkx2

Achievements

Achievement: QuickdrawAchievement: YOLOAchievement: Pull Sharkx2

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LegallyNotBlonde/README.md
  • 👋 Hi, there! I’m Sabrina.
  • 🤝 I'm a Data Analyst uncovering patterns, unlocking insights, and driving impact through data-driven solutions.
  • 👀 Interests: From history to sociology to AI and business analysis: I love diving into anything that sparks my curiosity.
  • 🌱 Enhancing my skills: Continuously improving in Data Analytics and Machine Learning with tools like Python, SQL, Tableau, and Data Engineering.
  • 💞️ Collaboration: I thrive in team environments where I can learn from others, share my own ideas and skills and help others.
  • 📫 How to reach me: LinkedIn | Email
  • 😄 Pronouns: she/her
  • 🎯 Fun Fact:
    I love creative cooking, taking classic recipes and giving them a unique twist (the results are always... interesting!). 🍲✨
  • ⭐ Why this GitHub is special:
    This is more than a collection of code: it's where I explore, create, grow, and share with joy. Every repository tells a story of skills learned, challenges overcome, and discoveries made. Let's connect, collaborate, and build something amazing together!

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  1. Movie_Analysis Movie_Analysis Public

    Analyzed 5,000+ movies with Pandas and Colab to build a machine learning model predicting movie revenue.

    Jupyter Notebook 1

  2. Tableau_Citi_Bike Tableau_Citi_Bike Public

    Analyzed Citi Bike data to uncover trends in ride duration, peak usage, and station demand, offering recommendations to optimize bike availability

    Jupyter Notebook

  3. MegaData_SparkProject_Home_Sales MegaData_SparkProject_Home_Sales Public

    This project used SparkSQL and PySpark to analyze home sales data, optimizing performance with caching and partitioning by build date.

    Jupyter Notebook

  4. Fire-Analysis Fire-Analysis Public

    Transformed wildfire data into SQL, leveraging Python, Pandas, and interactive JavaScript dashboards to uncover trends in wildfire frequency, damage, and economic impact (2008-2022).

    Jupyter Notebook 2

  5. credit-risk-classification credit-risk-classification Public

    Built a Logistic Regression model to predict loan risk, focusing on credit risk management with precision, recall, and F1-score evaluation

    Jupyter Notebook

  6. Crowdfunding_ETL Crowdfunding_ETL Public

    Built an ETL pipeline to extract, transform, and load crowdfunding data into PostgreSQL, using Python and Pandas for transformation and ensuring data integrity with foreign key constraints

    Jupyter Notebook