Real Estate Data Analysis

TRẦN BẢO NGỌC

Nam Tu Liem District, Hanoi, Vietnam – ***********@*****.*** – (+84)963.010.737

Education

Vietnam National University – International school Hanoi, Vietnam Degree: Pending Graduation Major: Business Data Analyst (BDA) Relevant Coursework: Advanced Data Analysis, Modern Data Mining, Seminar, Project, Database Systems, Python Programming, Data Analysis and Visualization, IT Project Management, E-commerce. Academic Projects:

1. Churn Customer Prediction (Python)

Description: First academic project focused on predicting customer churn using Python on Google Colab. Data: Telecom Churn Dataset from Kaggle, a fundamental dataset for analysis. Key Steps:

Performed basic data visualization directly in Colab.

Analyzed the correlation matrix to identify and remove highly correlated variables.

Built classification models using Random Forest and XGBoost to predict churn.

Evaluated model performance through a classification report and confusion matrix.

Applied GridSearchCV to optimize hyperparameters and improve model accuracy. Result: Random Forest accuracy: 0.93 XGBoost accuracy: 0.95 2. Hanoi Real Estate Prediction (Octoparse/SQL/HTML/Python) Description: This was a group project with the role of team leader focused on task delegation among team members, while responsibilities included handling web scraping and data analysis. Web scraping was conducted using Octoparse to collect real estate data, and Python was utilized for predictive modeling. Data: Raw real estate data collected from the website batdongsan.com.vn Key Steps:

Used Octoparse to scrape raw real estate data from batdongsan.com.vn.

Collected customer and demand data from social media platforms to enhance the prediction model.

Imported the scraped data into SQL for filtering and merging relevant information.

Applied Python to build a predictive model for house prices based on key features such as square footage, location, and number of rooms.

Developed an application that allows customers and investors to predict house prices, aiding in buying and selling decisions.

Results:

RMSE: 1.1156 R : 0.6774

The model predicted house prices with moderate accuracy. App: Unfortunately, the application was not successfully completed 3. Obstacle detection (Roboflow/Python)

Description: This project was developed to help visually impaired individuals walk safely on the streets and avoid obstacles such as potholes, cars, mud, and other hazards. The goal was to create a system that can detect obstacles in the environment and provide real-time feedback to the user. Data: Image of obstacles on Google

Key Steps:

Image Annotation: Imported images into Roboflow to annotate and label the obstacles (e.g., cars, potholes, puddles).

Model Training: Used Roboflow to create a custom object detection model and trained it using YOLOv8 (You Only Look Once) for efficient and real-time object detection.

Python Integration: Developed the obstacle detection system in Python, integrating the YOLOv8 model to identify and locate obstacles in images.

Testing and Optimization: Tested the system in real-world scenarios, optimizing for detection accuracy and real- time processing speed to ensure reliability in helping the visually impaired. TRẦN BẢO NGỌC

Results:

Obstacle Detection: The model successfully detected various obstacles such as trees and cars with relatively high accuracy.

Multiple Detections: Multiple detections of the same object were not significant, but this issue could be mitigated further by adjusting the Non-Maximum Suppression (NMS) threshold. Experience

FOX-AI JOINT STOCK COMPANY Hanoi, Vietnam

DATA ANALYST INTERN 6/2024 – 11/2024

Gained knowledge of large database structures, understanding how multiple interconnected tables form a unified data flow.

Learned how to link variables across different tables to establish relationships, which facilitated more accurate data analysis.

Used Power BI to analyze data, create interactive visualizations, and generate reports for better decision-making.

Developed proficiency in SAP and ERP tools, gaining insights into enterprise resource planning and integrated business processes.

Results:

Developed a better understanding of business operations and the responsibilities of software providers in supporting enterprises.

Enhanced data visualization skills, gained proficiency in Power BI, and familiarized with additional programming languages.

Skills & Interests

Skill: Research, Visualization, Data Processing, Prediction, Crawl Data. Language: Vietnamese, English.

Programming Languages: Python Basic experience with JavaScript, Golang, C, and C++. Tools: Excel, Word, Excel, Postman, Canva, Visual Studio Code, R, Google Colab, Power BI, Tableau.

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