Introduction This repository contains the implementation of a food security dashboard for predicting COVID-19 impact using Jupyter Notebook and Flask. The dashboard provides insights into food security trends during the COVID-19 pandemic based on data analysis and prediction models.

Usage Jupyter Notebook The Jupyter Notebook file contains the data cleaning, processing, analysis, and prediction models. It utilizes Python for data manipulation, visualization, and machine learning.

Flask Dashboard The Flask dashboard serves as the user interface for accessing food security predictions. It is built using HTML, CSS, and JavaScript. The dashboard interacts with the prediction models developed in the Jupyter Notebook to provide real-time insights.

Data Cleaning and Processing The data cleaning and processing steps include handling missing values, removing duplicates, and transforming raw data into a format suitable for analysis. Python was primarily used for these tasks.

Prediction Models Various machine learning models were developed to predict food security trends during the COVID-19 pandemic. These models were trained on historical data and evaluated for accuracy and performance.

Technologies Used Jupyter Notebook Python Flask HTML CSS JavaScript