Felipe Santos Borges

Projects

Things I’ve built.

A mix of data analysis, financial models, machine learning, and product work. Each project includes the process, the result, and what I learned.

  1. Exploring Asheville Airbnbs

    Asheville dashboard comparing entire-home supply, review coverage, prices, and monthly reviews.

    Using SQL, Excel, and Tableau to shortlist areas for a hypothetical travel company's accommodation partnerships.

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  2. Loan Default Risk Analysis

    Chart showing loan default rates falling as borrower credit scores rise.

    A SQL-first analysis of 601 personal loans to identify the borrower characteristics most associated with default.

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  3. CaseTrends: Immigration Intelligence

    CaseTrends product page showing a sample immigration case read and timeline.

    An end-to-end product build that turned public F2A applicant signals, official Visa Bulletin context, saved-case monitoring, and AI-assisted analysis into a working immigration intelligence tool.

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  4. Why We Buy Products

    Why we buy products according to LLMs: average epistemic-value scores from four scoring sources across 16,436 product reviews.

    I compared how four sets of LLM-generated scores interpreted the same 16,436 Amazon reviews across five types of consumer value—and found that model choice can change the result.

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  5. Disney DCF Valuation

    Valuation bridge from Disney enterprise value to estimated equity value.

    How I used Disney’s financial history to build a five-year Excel forecast and estimate the value of its future cash flows.

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  6. Predicting Titanic Survival

    ROC curves comparing logistic regression and decision tree predictions for Titanic survival.

    A compact machine-learning case study comparing logistic regression and a decision tree on the Titanic passenger dataset.

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