This repo contains implementation of IP2Vec model which is used for learning similarities between IP Addresses

Regression, Classification, Clustering, Dimension-reduction, Anomaly detection

- Graph Based Feature Selection is a new approach of reducing the dimensionality of a dataset using a Graph Based approach. - The apporach tries to generate a Kruskal's minimum spanning tree of a graph where the features of the dataset are the vertices and the correlation among them are the weights of the edges. -The edges having weights greater…

Reduce the curse of dimensionality

Tutorial- data Pre-processing

Application of PCA in facial recognition

This work involves two subtasks: assessing clustering results using all input variables and applying PCA for dimensionality reduction to improve understanding of multi-dimensional problems.

The pupose of this work is to create a model that helps predict the unsubscription (churn) of a given customer or a group of customers according to their age, gender, salary etc... using the provided data.

1st year master project: Projection of a 10-dimentional dataset into 2 or 3 dimentions using the Levenberg–Marquardt optimization algorithm, which was implemented.

Codes and Project for Machine Learning

This code is a part of a research project. It aims to identify the impact of the dimentionality reduction techniques on the accuracy and performance of machine learning based intrusion detection systems in IoT environments.

ML Homeworks using ML tools

This project focused on applying machine learning to build a clustering model to segment and analyze customer characteristics in the airline industry based on LRFMC scores using K-Means and suggest business strategy recommendations based on the results.

SDS course assignments

A newspaper articles classification system based on theme/topic using BERT (HuggingFace)

Clustering NBA Players Based on Performance

Fisher's LDA is a dimensionality reduction and classification method maximizing class separability by finding linear discriminants that optimize the ratio of between-class to within-class variance.

Data Mining and Wrangling Mini Project 3 - August 25, 2021

in this project, logistic regression, KNN, classification trees, random forests and neural network were used.