Fixes #704 coffee Bean Classification

Prediction Models/Coffee_bean_Classification/Readme.md

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+# Coffee Bean Classification with Deep Learning
+
+This project leverages deep learning to classify coffee bean types based on visual features. By training a convolutional neural network (CNN) model on labeled coffee bean images, we aim to create a system capable of identifying different types of coffee beans automatically.
+
+## Table of Contents
+
+- [Introduction](#introduction)
+- [Project Structure](#project-structure)
+- [Dataset](#dataset)
+- [Model](#model)
+- [Results](#results)
+
+## Introduction
+
+This project focuses on image classification using deep learning techniques to differentiate between various coffee bean types. This is particularly useful in industries that require high-quality control and consistent coffee bean quality.
+
+## Project Structure
+
+```plaintext
+├── data/                   # Dataset folder containing images
+├── notebooks/              # Jupyter notebooks for experimentation
+├── src/                    # Source files for model training and evaluation
+├── models/                 # Saved models and checkpoints
+├── results/                # Evaluation results and metrics
+└── README.md               # Project documentation
+```
+
+## Dataset
+The dataset contains images of coffee beans from different types. These images are preprocessed for uniformity, and are then split into training, validation, and testing sets.
+
+## Model
+We implemented a convolutional neural network (CNN) model for image classification. Key layers include:
+
+- Convolutional layers for feature extraction
+- Pooling layers to reduce dimensionality
+- Dense layers to classify images based on extracted features
+
+## Results
+The model's performance is evaluated using metrics such as accuracy, precision, recall, and F1-score on the test dataset. The model achieves satisfactory results in distinguishing between coffee bean types.
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