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Be1an001/README.md

Hi, I'm Cheng Liu 👋

Analytics graduate from Northeastern University, Silicon Valley (Applied Machine Intelligence, GPA 3.93). Previously a Java software engineer in Taipei. Now focused on data analysis, machine learning, and building decision-support tools that non-technical stakeholders can actually use.

🛠️ Tech Stack

Languages

Python SQL R Java

ML & Analytics

scikit-learn XGBoost Pandas SHAP

Tools & Platforms

Streamlit Tableau MySQL Git

📌 Featured Projects

🚀 Salifort Retention Risk Explorer A 9-page Streamlit decision-support app extended from a notebook attrition analysis. Includes PACE Navigator and an MLOps Lab covering FastAPI, Docker, MLflow, Airflow scaffold, and CI. 🔗 Live Demo

📊 Pharmacy Claims Data Warehouse Star schema design in MySQL with dimension/fact tables, foreign-key constraints, and CTE + window-function reporting queries.

🔬 Semiconductor Pass/Fail Prediction Leakage-safe ML workflow on UCI SECOM sensor data with class-imbalance handling and threshold tuning.

✈️ Nvidia Risk Management Analysis Portfolio version of my ALY6130 project on NVIDIA risk management using risk scoring, heat maps, scenario modeling, and Monte Carlo simulation.

🚗 Waze Churn Modeling Five-model comparison with calibration review, threshold tuning, and CatBoost SHAP explainability.

🌱 Background

I took a non-linear path from advertising design, field work, information management, Java engineering, to a master's in analytics in the US. Each step added something useful: engineering rigor from the Java work, stakeholder communication from sponsor projects, and a habit of asking what the result is actually for.

🎯 Currently

  • 🔍 Looking for Data Analyst, BI, and applied ML roles in Taiwan
  • 📚 Working on Google Business Intelligence Certificate

📍 Taiwan  |  📧 akbakb480000@gmail.com  |  🔗 LinkedIn  |  🚀 Live Demo App

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  1. nvidia-risk-management-analysis-python nvidia-risk-management-analysis-python Public

    Portfolio version of my ALY6130 project on NVIDIA risk management using risk scoring, heat maps, scenario modeling, and Monte Carlo simulation.

    Jupyter Notebook

  2. salifort-motors-attrition-modeling-python salifort-motors-attrition-modeling-python Public

    Cost-aware employee attrition modeling project based on the Salifort Motors case, with operational and survey-rich modes, SHAP explainability, and HR-focused retention insights.

    Jupyter Notebook

  3. nyc-taxi-generous-tipper-classification-python nyc-taxi-generous-tipper-classification-python Public

    Public portfolio rewrite of the Automatidata project using official NYC Open Data, Colab, and XGBoost to predict generous tipper trips.

    Jupyter Notebook

  4. salifort-retention-risk-explorer-streamlit salifort-retention-risk-explorer-streamlit Public

    Streamlit app for operational HR attrition screening and decision support based on the Salifort Motors portfolio case.

    Python

  5. secom-fail-screening-streamlit secom-fail-screening-streamlit Public

    Interactive Streamlit portfolio app for SECOM semiconductor fail-screening benchmark, threshold trade-off analysis, explainability, and MLOps-lite demonstration.

    Python

  6. vertex-ai-credit-card-fraud-case-study vertex-ai-credit-card-fraud-case-study Public

    Portfolio case study from EAI6020 using Vertex AI AutoML for credit card fraud detection, with precision-recall evaluation, threshold selection, and business trade-off analysis.