Simple Application of ANN for Apple Quality Prediction

Introduction

In the world of machine learning, Artificial Neural Networks (ANNs) have become a powerful tool for a variety of predictive tasks. One fascinating application is using ANN to predict the quality of apples based on specific features. This blog post will walk you through a simple implementation of ANN to predict apple quality, highlighting the process from data preparation to model evaluation.

Dataset Overview

Our dataset contains several key features that describe the characteristics of apples:

1. A_id: Unique identifier for each fruit
2. Size: Size of the fruit
3. Weight: Weight of the fruit
4. Sweetness: Degree of sweetness of the fruit
5. Crunchiness: Texture indicating the crunchiness of the fruit
6. Juiciness: Level of juiciness of the fruit
7. Ripeness: Stage of ripeness of the fruit
8. Acidity: Acidity level of the fruit
9. Quality: Overall quality of the fruit
10. The goal is to predict the Quality of apples using the other features as inputs to our ANN.

Acces Code here: Google Colab