This project explores the use of different neural network architectures on the Iris dataset to classify flower species. The dataset is sourced from Kaggle. Table of Contents:

This project implements a neural network from scratch to help a gardener classify Iris flowers into three species: Setosa, Versicolor, and Virginica. The network analyzes four measurements (sepal length, sepal width, petal length, and petal width; all in cm) to make its predictions.

Apr 5, 2022 · Rosenblatt laid the foundations for artificial neural networks that can be trained and can produce an output when new information is presented [3]. This article aims at creating a perceptron in Python from scratch and performing training and testing on the Iris dataset.

This repository contains the code for implementing an Artificial Neural Network (ANN) on the Iris dataset using Google Colab. The code is written in Python using the Keras library. Platform - Google Colab.

Mar 13, 2025 · A Simple Neural Network in Keras + TensorFlow to classify the Iris Dataset Following python packages are required to run this file: pip install tensorflow pip install scikit-learn pip install keras

Along this notebook we'll explain how to use the power of cloud computing with Google Colab for a classical example – The Iris Classification Problem – using the popular Iris flower dataset....

Apr 6, 2025 · In order to achieve such a task, we need to implement an algorithm that is able to classify the iris flowers into their corresponding classes. Luckily we don't need to hardcode the algorithm for classification since there are already many algorithms available in …

Mar 17, 2022 · In this tutorial we will practice artificial neural network using one of the most simple Datasets in the World of Data Science. We will use characteristics of the flower Iris to predict the...

Apr 10, 2023 · In this blog article, we will guide you through the process of building a multilayer neural network from scratch to classify the Iris dataset step by step. The first step in any machine...

Jan 8, 2023 · There are three species we will train this model to identify: Iris Setosa, Iris Versicolor, and Iris Virginica. Before we start looking at code, lets take a step back and outline the structure of a fully connected neural network (also known as a multilayer perceptron or MLP). Put simply, there are three ‘sections’.