Machine Learning
CS 253A Course Assignment in Machine Learning
Table of Contents
About The Project
This is a course project for CS 253A under Profesor Mr. Indranil Saha related to machine learning algorithm. In this project I implemented an spam Detector Model using SVM(Support Vector Machine) and KNN(K-Nearest Neighbors) Algorithm in python.
Built With
Getting Started
- The datasets has been uploaded using Kaggle Datasets.
- The code outputs the plot for the frequency of different vocabularies used as well as the accuracy of the machine learning model created.
Prerequisites
- To run the script files one needs to install Jupyter Notebook along with Anaconda3 in their computer.
- Now simply open the Jupyter Notebook and run each code block of the programe.
Assumptions
- Note that the spam_or_not_spam.csv file should have data in correct format present in it, i.e. each row must contain only 2 column namely email and label with label being either 0 or 1. Thus no empty column should present.