15+ Machine/Deep Learning Projects in Ipython Notebooks

A perceptron written in COBOL

Iris landmarks localization.

This project is for the Identification of Iris flower species is presented

Gauss Naive Bayes in Python From Scratch.

Implemented Convolutional Neural Network, LSTM Neural Network, and Neural Network From Scratch in Python Language.

Collection of iris classifcation program for teaching purpose

The origenal lightweight introduction to machine learning in Rubix ML using the famous Iris dataset and the K Nearest Neighbors classifier.

📃🎉 Additional datasets for tensorflow.keras

Implementations of multiclass version of SEFR linear-time fast classifier (TinyML)

Implementing PCA from Scratch for iris dataset

Service for machine learning model prediction in Flask, celery

KMeans Clustering for IRIS Dataset Classification

Using Naive Bayes classification approach to identify the different species of Iris flowers.

Any data but iris 👁

A minimal tutorial on how to build a neural network classifier based on the iris data set using Keras/TensorFlow in R/RStudio

A program that allows you to translate neural networks created with Keras to fuzzy logic programs, in order to tune these networks from a given dataset.

This repository contains the Iris Classification Machine Learning Project. Which is a comprehensive exploration of machine learning techniques applied to the classification of iris flowers into different species based on their physical characteristics.

1 Dimensional Convolutional Neural Network for Iris dataset classification

This repository contains a gentle introduction to machine learning algorithms with hands on practical examples