TimeSeriesForecasting

Übersicht

TimeSeriesForecasting is an end-to-end project for analyzing and forecasting time series data using Python. The project utilizes Jupyter Notebooks for data analysis, Python scripts for data processing and modeling, and Docker to provide a consistent development environment.

Projektstruktur

TimeSeriesForecasting/
├── data/
├── notebooks/
├──── DeepLearningApproaches/
├──── GenerativeAIApproaches/
├──── MachineLearningApproaches/
├── models/
├── results/
├── requirements.txt
├── .gitignore
└── README.md

• data/: Contains the raw data.
• notebooks/: Jupyter Notebooks for data analysis and modeling.
• scripts/: Python scripts for various tasks.
• models/: Saved models.
• results/: Results and reports.
• requirements.txt: List of required Python packages.
• .gitignore: Files and directories to be ignored by Git.
• README.md: Project description and instructions.

Installation

Steps

1. Clone the repository:

   git clone <repository-url>
   cd TimeSeriesForecasting

Nutzung

1. Place your raw data in the data/ directory.
2. Create and edit Jupyter Notebooks in the notebooks/ directory.
3. Save models in the models/ directory.
4. Store results and reports in the results/ directory.

Autor

Sangeeths Chandrakumar