Shirlyngit/NAIROBI-HOUSE-PRICE-PREDICTION
Domain:
socioeconomicRecord type:
project
Creator:
Shi
Host:
Built a machine learning system to predict the house prices for different houses, apartments and rentals in Nairobi Metropolitan area - Kenya.
## FLASK_APP SCREENSHOT
# 🏡NAIROBI-HOUSE-PRICE-PREDICTION-SYSTEM
OBJECTIVE: Build a Predictive Machine Learning System to predict the house prices in different demographic areas within Nairobi Metropolitan area - Kenya. Then build a ChatBot for user engagement with this Housing prices information.
🛠️ Tools, Frameworks, and Technologies:
- Python
- Machine Learning Libraries: Scikit-learn, TensorFlow, PyTorch
- Data Manipulation: Pandas, Numpy
- Visualization: Matplotlib
- Web Frameworks: Flask, FastAPI, or Streamlit. Used Flask
- APIs: OpenAI APIs
🔍 Project Overview:
1. Web Scraping: Scrape relevant sites to gather house data.
2. Data Cleaning: Clean and preprocess the data.
3. Exploratory Data Analysis (EDA): Analyze and visualize the data.
4. Modeling: Build and train the predictive models.
5. Deployment: Deploy the model using a web framework.
6. Chatbot Creation: Develop an RAG chatbot, using OpenAI APIs, for user engagement that provides housing information in Kenya.
🗂️ Repository Structure:
- 📁 data: Main folder housing all other subfolders.
- 🤖 chatbot: Subfolder containing the implementation details of the chatbot.
- 🧹 cleaning_eda_modeling: Contains Jupyter notebooks for data cleaning, EDA, and modeling. Also includes the cleaned CSV file ready for modeling.
- 📂 data_collection: Subfolder with web scraping scripts and the gathered data.
- 🚀 inferencing_and_deployment: Contains inferencing scripts, the flask_app.py script, and the respective requirements.txt file.
- 💾 model_preprocessor_weights: Contains the base model and fine-tuned model pickle files along with the preprocessor pickle file.
- 🚧 Project Status:
For more detailed explanations, refer to the README.md files within each subfolder.
🚀 Skills Utilized & Acquired:
🐍 Python for Data Science: Leveraged Python's powerful libraries for data manipulation, analysis, and modeling.
🌐 Web Scraping: Extracted valuable data from relevant real estate websites.
🧠 Domain Knowledge & Feature Engineerin …