Traffic Accident Analysis using python machine learning

This is a very Important part of Data Science Case Study because Detecting Frauds and Analyzing their Behaviours and finding reasons behind them is one of the prime responsibilities of a Data Scientist. This is the Branch which comes under Anamoly Detection.

Imbalanced Intent classification model with deployment

Machine learning is used to analyze and predict attrition flags in credit card customers.

Course Project for CS273A: Machine Learning at UCI

Facial skin disease detection using Neural Networks

Data Science Classification General Notebook

Machine Learning analysis for an imbalanced dataset. Developed as final project for the course "Machine Learning and Intelligent Systems" at Eurecom, Sophia Antipolis

Prediction module for Tumor Teller - primary tumor prediction system

Our goal was to create a ML bot that analyzes real time trading data to determine the most opportune times buy and sell stock

An analysis on credit risk

The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.

Portfolio of my data science projects which i have completed for learning, skill development .

Building a tabular binary classification neural network to predict Telco's Customer Churn from their publicly available dataset on Kaggle.

Text classification with scikit-learn, used to make predictions for Kaggle Spooky Author Identification competition

Utilizing machine learning to examine deforestation rates in the undeveloped region of Paraguay's Chaco

2023년 11월 대한산업공학회(UNIST) : 다중 역할 경험을 고려한 게임 유저 이탈 예측: 롤 게임을 중심으로, 1저자

Using Scikit-learn and Imbalanced-learn to build and evaluate ML models that predict credit risk

Use Random Forest to prepare a model on fraud data. Treating those who have taxable income <= 30000 as "Risky" and others are "Good" and A cloth manufacturing company is interested to know about the segment or attributes causes high sale.

Successfully trained a machine learning model which can predict whether a given transaction is fraud or not.