Final project based on text classification by emotions using machine learning models and BERT.

Klasifikasi Biner dan Multikelas untuk dataset penjualan pada sebuah supermarket

This project focuses on building a fraud detection model for credit card transactions using a dataset containing transactions made by European cardholders in September 2013. We are working with a highly unbalanced dataset and the challenge lies in effectively detecting fraudulent transactions while minimizing false positives.

이화여자대학교 컴퓨터공학과 19-2,20-1 캡스톤프로젝트

Data Project

Here you can explore different projects around Machine Learning Algorithms, Enjoy ☺️

flask website that automatically assigns multiple relevant tags to a Stackoverflow question

A financial institution wants to accurately predict the probability of loanee/borrower defaulting on a vehicle loan in the first EMI on the due date.

The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 150.

Fake reviews Detection using SGD Classifier

implementation of basic ML algorithms

Supervised and unsupervised algorthimn analysis on APS Failure at Scania Trucks Dataset

A sentiment analysis project using linear support vector machine with stochastic gradient descent method. Built to analyze whether the tweet sentiment are happy or sad.

Fake News Detection using SGD Classifier

This project performs analysis and experimentation with classifiers in Python using the MNIST dataset, which consists of images of handwritten digits.

The implications of hate speech have received considerable attention from the common public and society as a whole. There has been a rising concern over the effects of hate speech and offensive language. However, much of this attention is focused on the critical presentation and evaluation of arguments in favor of and against the ban on hate spe…