IE224.P11.CNCL - Data Analysis

Course Information

• Course: IE224.P11.CNCL - Data Analysis
• Lecturer: Pham The Son
• Semester: 1, 2024-2025

Team Information

No.	Student ID	Full Name	Field of Study
1	21521049	Ho Quang Lam	Information Systems (HTTT)
2	21521882	Le Minh Chanh (Leader)	Information Systems (HTTT)
3	21522722	Tran Thi Thanh Truc	Computer Networks and Communications (MMT&TTDL)

Project Information

• Project Title: ANALYSIS AND MODEL DEVELOPMENT FOR WEATHER FORECASTING IN DISTRICTS OF HO CHI MINH CITY
• Dataset: HCMCityWeather.csv (last updated: 26/10/2024)

Overview dataset

• Collected from the Open-Meteo Historical Weather API, based on the coordinate data of 22 districts, towns, and cities in Ho Chi Minh City, gathered from the Nominatim | OpenStreetMap Website.
• Size: 80.388 rows x 29 columns
• The attributes include recorded weather parameters such as temperature, humidity, wind direction, rainfall, cloud cover, and more.

Summary

• Objective: To analyze and develop models for weather forecasting in districts of Ho Chi Minh City.
• Algorithm: Random Forest, XGBoost, LightGBM
• Tasks:
  • Data preprocessing: Clean, transform, and visualize the dataset.
  • Exploratory Data Analysis (EDA): Analyze the dataset to gain insights into the weather patterns.
  • Model development: Develop a model to predict the probability of rain for the next day in the districts of Ho Chi Minh City. (Classification problem)
  • Model evaluation: Evaluate the model's performance using appropriate metrics.
  • Model deployment: Deploy the model as a web application for users to access and interact with.

Technology:

• ipynb: Pandas, Numpy, Scikit-learn, Matplotlib, Seaborn, Xgboost, Lightgbm
• Website: Streamlit