Highlights:
- Anaylzed KNN, Naive Bayes, SVMs and Neural Networks and finally implemented Naive Bayes and KNN for the classification of various data sets into spam and ham using Keras, Pandas, Numpy and Scikit-learn
- Compared accuracies for various data sets and categorised the best method for each data set
Details:
My interest in Applied Machine Learning was first kindled during my research stint at the Indian Institute of Technology Kanpur under Professor Vipul Arora, of the Electrical Engineering Department, just after my first year of Undergraduate Study. My presentation on my findings received special mention from the Professor, and I recieved a Letter of Recommendation for my work.
To run the code:-
-
run the command "python3 knn.py" for K-nearest neighbours algorithm and "python3 naive_bayes.py" for naive bayes algorithm on command line and you will get to see the accuracies for the dataset.
-
emails.csv is the dataset used.