/Predicting-Projects-with-FBprophet-Python

This is repo where you'll find interesting Machine learning projects. Basically we've used FBprophet and Python to predict or forecast any trend or data based on time series analysis. All the datasets and codes are attached here

Primary LanguageJupyter Notebook

Prediction Projects using FBProphet & Python

This repository contains a collection of prediction projects developed using the FBProphet library in Python. FBProphet is a powerful time series forecasting tool developed by Facebook, designed to handle various time series forecasting tasks with ease.

Table of Contents

  1. Introduction
  2. Installation
  3. Usage
  4. Projects
  5. Contributing
  6. License

Introduction

Time series forecasting is a crucial aspect of data analysis, providing valuable insights into future trends and patterns. FBProphet is a popular open-source library that simplifies the process of time series forecasting, making it accessible to both beginners and experienced data scientists.

This repository aims to showcase various prediction projects implemented using FBProphet in Python. These projects cover a wide range of applications, from financial forecasting to weather predictions and more. You can explore and learn from these projects to understand how to leverage FBProphet for your own time series forecasting tasks.

Installation

To get started with the projects in this repository, you'll need to install the necessary dependencies. You can do this by setting up a Python environment and installing the required libraries using pip. Here are the basic installation steps:

  1. Clone this repository to your local machine:

    git clone https://github.com/AdadAlShabab/Predicting-Projects-with-FBprophet-Python.git

  2. Navigate to the project directory:

    cd predicting-projects-with-fbprophet-python

  3. Create a virtual environment (optional but recommended):

    python -m venv venv

  4. Activate the virtual environment:

    • On Windows:

      venv\Scripts\activate

    • On macOS and Linux:

      source venv/bin/activate

  5. Install the required packages:

    pip install -r requirements.txt

Usage

Each prediction project in this repository is organized in its own directory. To use a specific project, navigate to the project's directory and follow the project-specific instructions provided in the project's README file.

Additionally, you can use the provided Jupyter notebooks or Python scripts to explore and run the forecasting models with FBProphet.

Projects

Here's a list of prediction projects included in this repository:

  1. [Financial Market SAles Price Prediction]

    • Forecasting sales prices and trends.

  2. [North America's Cancer Prediction]

    • Predicting Cancer forecast.

  3. [Tempurature Prediction.]

    • Forecasting temperature of next 400 days.

[** Stay tuned for more →**]

Contributing

We welcome contributions from the community to add more prediction projects or improve existing ones. If you'd like to contribute, please follow the guidelines outlined in CONTRIBUTING.md.

Feel free to reach out if you have any questions or suggestions. Happy forecasting with FBProphet! 📈🔮