Machine learning model for Credit Card fraud detection

Spam detection in SMS messages with BERT model and Machine Learning algorithms

The aim to decrease the maintenance cost of generators used in wind energy production machinery. This is achieved by building various classification models, accounting for class imbalance, and tuning on a user defined cost metric (function of true positives, false positives and false negatives predicted) & productionising the model using pipelines.

Predict the enzyme class of a given FASTA sequence using deep learning methods including CNNs, LSTM, BiLSTM, GRU, and attention models along with a host of other ML methods.

Electricity Fraud Detection in Smart Grids

System to tell apart the transaction was from the real user who owns the credit card or the transaction was from the stolen credit card.

An implementation of SMOTE

Predicting the ability of a borrower to pay back the loan through Traditional Machine Learning Models and comparing to Ensembling Methods

A compilation of codes for SMA, DC, ADS

Credit Card fraud detection

使用比赛方提供的脱敏数据，进行客户信贷流失预测。

Repository for "Data Mining - Advanced Topics and Applications" projects exam.

Obstructive Sleep Apnea classification with help of numerical data set which having the physical body characteristics with the help of machine learing

A model that recommends University based on details of an applicant.

Prediction of basic soil nutrients (phosphorus, potassium, boron, calcium, magnesium and manganese) using reflectance from Hyperspectral Satellite Images (HSI).

This project provides a comprehensive analysis of the Eurovision Song Contest, with insights derived from both traditional statistical methods and machine learning techniques.

Gear detection using OpenCv and Machine Learning

This project is a part of the research on PolyCystic Ovary Syndrome Diagnosis using patient history datasets through statistical feature selection and multiple machine learning strategies. The aim of this project was to identify the best possible features that strongly classifies PCOS in patients of different age and conditions.

RCSMOTE: Range-Controlled Synthetic Minority Over-sampling Technique for handling the class imbalance problem