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Profbla2020/README.md

Hi there, I'm Luqman Adeola. 👋

🌟 About Me

I'm a passionate Data Analyst with a strong background in extracting insights from complex data sets. I specialize in using Python, R, SQL, and various business intelligence tools like Power BI and Excel to drive data-driven decision-making. I love automating processes with Power Apps and Power Automate, ensuring efficiency and accuracy in data workflows.

  • 🔭 I’m currently working on projects related to Machine Learning, Generative AI, Survival Analysis, Statistical Analysis, Dashboards, Automation, and Business Intelligence (BI).
  • 🌱 I’m currently learning advanced techniques in "Machine Learning with Python and R", "Time Series Forecasting", "Power APP and Automation".
  • 👯 I’m looking to collaborate on projects involving machine learning, generative AI, survival analysis, statistical analysis, dashboard creation, and automation. I'm particularly interested in contributing to open-source projects that focus on data science, AI-driven analytics, and business intelligence tools.
  • 💬 Ask me about data analysis, automation, and visualization.
  • 📫 How to reach me: [email protected]
  • 😄 Pronouns: he/him
  • ⚡ Fun fact: I love turning raw data into compelling stories as well as coffee enthusiast who codes better with a good brew.

🛠️ Tools & Technologies

Here are some of the tools and technologies I work with:

Programming Languages

  • Python: Pandas, NumPy, Matplotlib, Seaborn
  • R: dplyr, ggplot2, Shiny
  • SQL: MySQL, PostgreSQL, Microsoft SQL Server

Data Visualization & BI Tools

  • Power BI: Dashboard creation, DAX, Power Query
  • Excel: Advanced formulas, Pivot Tables
  • Tableau: Data visualization, storytelling

Data Management & Automation

  • R Studio: Data analysis and visualization
  • Power Apps: Custom app development
  • Power Automate: Workflow automation

🧰 Projects

Here are some projects that showcase my work:

Project 1: Hedonic Price Model for Impact of Micromobility infrastructure on Property Values

Regression and Hedonic Price Modeling: Using R to conduct sophisticated statistical analyses that control for various property characteristics, ensuring that the observed effects on property prices are attributed accurately to micromobility proximity

Project 2: Customer Next Buy Analysis Model

An Unsupervised Machine Learning project using Python to Predict customers that would buy again based on purchasing behavior.

📈 GitHub Stats

Your GitHub stats

📫 Connect with Me

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  1. Profbla2020 Profbla2020 Public

    Config files for my GitHub profile.

  2. AMR-TEAM AMR-TEAM Public

    This document presents an analysis of global and regional antimicrobial resistance (AMR) trends for 13 WHO priority list pathogens using ATLAS data collected from 2004 to 2021.

    2

  3. Customer-predictive-Model Customer-predictive-Model Public

    NextBuyPredictor is a machine learning project designed to predict whether a customer will make their next purchase within a specified timeframe. By analyzing customer purchase history and behavior…

    Jupyter Notebook

  4. Hedonic-Price-Model-project Hedonic-Price-Model-project Public

    The project focuses on a critical and timely theme: assessing the impact of micromobility infrastructure on property values in London. This study sits at the intersection of urban planning, real es…

    HTML

  5. Raod-Accident-Dashboard- Raod-Accident-Dashboard- Public

    This project features an Excel-based interactive dashboard that visualizes comprehensive road accident data. The dashboard provides insights into fatal, serious, and slight casualties, along with d…

    1

  6. Road-Accident-in-Nigeria Road-Accident-in-Nigeria Public

    The dataset records the total number of road traffic accidents in each state for the given period, categorizing the accidents into fatal, severe, and minor incidents. This comprehensive dataset is …