To classify the species of Iris with its given specification and training an model to recognise them

Introduction to data versioning with DVC through the "Hello World" of machine learning: Iris flower classification.

Perceptron Multicapa (MLP) clasificación - Multilayer Perceptron (MLP) for multi-class classification for iris dataset

Simple ML system for the iris problem

A basic Machine Learning models (trained on Iris dataset) serving API

An analysis on Iris dataset of Scikit learn

The aim of this project is to develop a biometric system for identifying individuals using the iris allowing, through a graphical interface, to introduce an iris image and to display, after the processing steps, the identity of the person identified in the database.

Decision tree classifier on different dataset.

Principal Component Analysis on different dataset.

Data-Analyst-Project-Series

Logistic Regression

Explore the Iris dataset through interactive visualizations using R and Plotly

Explore the Iris dataset through interactive visualizations using R and Plotly to uncover patterns and insights in flower species data

Iris flower classification using KNN and Random forest algorithm

My recent exploration into Principal Component Analysis (PCA) on a well-known Iris Flower Dataset!

An exploratory data analysis and machine learning project using the Iris dataset to classify flower species with a K-Nearest Neighbors classifier. It includes data visualization, feature scaling, model training, and evaluation with 100% accuracy on the test set.

Machine learning project for classifying iris flowers using the Iris dataset with PyTorch and Python.

C language Implementation of the Kmeans Clustering Algorithm

This repository contains the implementation of the Logistic Regression algorithm for classifying the Iris dataset using the One-vs-Rest (OvR) approach, developed with Python 3.12 and TensorFlow v2.16.

Classifies irises into one of 3 species: Setosa, Versicolor, Virginica.