Code and other material for Naive Bayes KS
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Updated
Mar 12, 2017 - Jupyter Notebook
Code and other material for Naive Bayes KS
Using k-Nearest Neighbors algorithm, training it using 2/3rd of the iris.data and using the rest of the 1/3rd for the test case, and yield prediction for those 1/3rd with an accuracy usually greater than 90% , and this algorithm is implemented without using Python scikit-learn.
Repository contains deep learning projects
The following code uses 5 different machine learning algorithm on the Iris dataset to predict the species of the flower
Implementation of K-Means clustering algorithm in python
Iris flower classification among setosa, verginica and versicolor.
Sample tensorflow implementation for predicting iris
This is a classification of iris flower using k nearest neighbour classifier
Higher Diploma in Science in Computing (Data Analytics) - Programme Module: Programming and Scripting (COMP08049)
Exploring the Iris Flower Data Set with scikit-learn
Simple Classification program to predict the species of an iris flower.
This project is for the Identification of Iris flower species is presented
Visualização de dados com a biblioteca Matplotlib - Python
Iris data set analysis for Udacity.
Implementation & Learning of Iris Data-set and use of various Machine learning Algorithm
If you liked my analysis, pls upvote my notebook!
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