Time Series Forecasting Project

This project is designed for time series forecasting using various models. It allows you to input time series data, generate forecasts, visualize results, configure model parameters, perform hyperparameter tuning, validate models, and download forecasts and trained models.

Table of Contents

• Images
• Getting Started
  • Prerequisites
  • Installation
• Usage

Images

Getting Started

Prerequisites

Before you begin, ensure you have met the following requirements:

• Python (>=3.6)
• Required Python libraries (specified in requirements.txt)

Installation

1. Clone this repository:

   git clone https://github.com/JatinSingh28/Forecast.git
   

2. Change directory:

   cd Forecast
   

3. Install requirements:

   pip install -r requirements.txt
   

4. Run streamlit app:

   streamlit run main.py 
   

Usage

1. Generating Forecasts
2. Visualizing Results
3. Parameter Configuration
4. Model Validation
5. Hyperparameter Tuning
6. Download Forecast
7. Download Trained Model