Python-based web application, Flask platform, utilizes a powerful Content-Based Filtering Algorithm to provide personalized recommendations excercises

PCA applied on images and Naive Bayes Classifier to classify them. Validation, cross validation and grid search with multi class SVM

In this repository, we will explore different classification models to predict whether a user will purchase a product based on age and estimated salary.

This code reads a dataset i.e, "Heart.csv". Preprocessing of dataset is done and we divide the dataset into training and testing datasets. Linear, rbf and Polynomial kernel SVC are applied and accuracy scores are calculated on the test data. Also, a graph is plotted to show change of accuracy with change in "C" value.

Created a model from scratch (without using any libraries) to predict whether a person have a heart diseases using support vector machine. and then compare the model's accuracy with model created using Sklearn library.

Loan approval system using svm

Second assignment of Artificial Intelligence course held by Professor Andrea Torsello of Ca' Foscari University of Venice, spam detectors with SVM classification using linear, polynomial of degree 2, RBF kernels and Naive Bayes and k-NN