Alt Link for Notebook:- https://nbviewer.jupyter.org/github/kartikparashar786/Support-Vector-Machine-Project/blob/main/Support%20Vector%20Machine%20Project.ipynb?flush_cache=True

Support-Vector-Machine-Project

This Model is created using SUPPORT VECTOR MACHINE in PYTHON 3.9. The model is based on famous Iris data set and the prediction of species with help of its features.

Getting Started

You need to have a python platform on your system.

• Download all the files in your pc but make sure to keep all of them in the exact same folder , or you can clone the repository.
• Open Support Vector Machine Project .ipynb file.
• Later, hit run and the code will start executing.

Modules/Libraries used

The python libraries I used are-

• IPython
• Pandas
• Seaborn
• Numpy
• Matplotlib
• ScikitLearn

Data set

Data Set is the famous Iris flower data set. The Iris flower data set or Fisher's Iris data set is a multivariate data set introduced by Sir Ronald Fisher in the 1936 as an example of discriminant analysis. The data set consists of 50 samples from each of three species of Iris (Iris setosa, Iris virginica and Iris versicolor), so 150 total samples. Four features were measured from each sample: the length and the width of the sepals and petals, in centimeters. We Focus on the following three Species:

Links

• Linkedin - www.linkedin.com/in/kartik-parashar-90bb1a1a4
• Gmail- kartikgparashar786@gmail.com
• Kaggle - https://www.kaggle.com/kartikparashar
• HackerRank- https://www.hackerrank.com/Blu_Dragon
• This Repo- https://github.com/kartikparashar786/Support-Vector-Machine-Project

Made by-Kartik Parashar