Iris flower classification project: Leveraging machine learning for precise botanical identification

Abstract

This research paper proposes the development of an advanced classification model for the Iris Flowers dataset, utilizing DL techniques such as (CNNs) and (RNNs). The purpose of this article is to investigate the effectiveness of deep learning models in task classification compared to traditional machine learning algorithms. The project includes pre- processing the Iris Flowers dataset, building a deep learning model for classification, and comparing its performance to traditional machine learning algorithms. The paper's outcomes will provide insights into the potential of advanced deep learning techniques in modern data science.