https://github.com/pipe199x/end-to-end-prediction-california

End-to-end prediction project using various technologies to predict housing prices in California.
https://github.com/pipe199x/end-to-end-prediction-california

california-housing data-analysis machine-learning python

Last synced: 6 days ago
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End-to-end prediction project using various technologies to predict housing prices in California.

• Host: GitHub
• URL: https://github.com/pipe199x/end-to-end-prediction-california
• Owner: Pipe199x
• Created: 2024-06-08T16:41:33.000Z (5 months ago)
• Default Branch: master
• Last Pushed: 2024-06-08T16:47:49.000Z (5 months ago)
• Last Synced: 2024-06-09T17:47:08.082Z (5 months ago)
• Topics: california-housing, data-analysis, machine-learning, python
• Language: Jupyter Notebook
• Homepage:
• Size: 2.05 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# END-TO-END-PREDICTION-CALIFORNIA

This project uses various technologies to predict housing prices in California. The project involves data preprocessing, visualization, and machine learning model training to make accurate predictions. Below are the main components and technologies used in the project:

## Technologies Used

- **Python**: The programming language used to write data processing and analysis scripts.

- **Pandas**: A Python library for data manipulation and analysis.

- **Matplotlib** and **Seaborn**: Libraries for data visualization.

- **Scikit-learn**: A machine learning library for model training and evaluation.

## Project Description

The goal of this project is to process and analyze housing data to predict housing prices in California. The data includes various features such as location, number of rooms, and median income. The project involves data cleaning, exploratory data analysis (EDA), and building predictive models using machine learning algorithms.

### Project Structure

- **housing.csv**: The dataset containing housing data for California.

- **the-ultimate-end-to-end-prediction.ipynb**: The Jupyter notebook containing the data preprocessing, visualization, and model training scripts.

- **images/**: Contains images used for visualizations.

  - `CA.png`: Map of California.

  - `SFM.png`: San Francisco map.