15+ Machine/Deep Learning Projects in Ipython Notebooks
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Updated
Apr 3, 2020 - Jupyter Notebook
15+ Machine/Deep Learning Projects in Ipython Notebooks
A perceptron written in COBOL
This project is for the Identification of Iris flower species is presented
Iris landmarks localization.
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 original 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.
This repository contains a gentle introduction to machine learning algorithms with hands on practical examples
1 Dimensional Convolutional Neural Network for Iris dataset classification
Add a description, image, and links to the iris-dataset topic page so that developers can more easily learn about it.
To associate your repository with the iris-dataset topic, visit your repo's landing page and select "manage topics."