Our project utilizes machine learning models to predict cardiovascular diseases (CVDs) by analyzing diverse datasets and exploring 14 different algorithms. The aim is to enable early detection, personalized interventions, and improved healthcare outcomes.

Identifying Giants and Dwarfs Stars through Machine Learning

MlFlow Project creating pipelines and using Grid-Search Cross Validation to find optimal parameters for Old School Runescape Machine Learning datasets.

Bank Churn Classification

데이콘 신용카드 사용자 연체 예측 AI 경진대회 코드

Credit card fraud detection using various sampling methods and machine learning algorithms.

With imbalanced observed data, a search for the best model is conducted. The bank is seeing its customers leave. Wondering if there are patterns to their decision to exit, the bank wishes to anticipate for this trend. When the positive class is the minority in an imbalanced dataset, a model need to be trained for robustness.

Interconnect seeks to forecast customer churn by analyzing package choices and contracts. If a customer plans to leave, they're offered unique codes and special packages to foster loyalty.

This project tackles the growing concern of obesity by developing a model to predict an individual's risk. By analyzing various factors, we aim to identify people who might be more susceptible to weight gain and related health problems.

Practicum Workshop

Rank 89 Solution for Analytics Vidhya Jantahack Customer Segmentation

HackerEarth Machine Learning Problem solved with ❤️ by Nakshatra Singh.

In this project, I worked on a classification problem using an imbalanced dataset which predicts ecological footprints. The aim of the project was not necessarily to build a classification model but to investigate the different methods of correcting an imbalanced dataset in order not to build a biased classifier

This repository features my Kaggle projects, highlighting advanced techniques in data preprocessing, feature engineering, model selection, and optimization across various competitions.

Fichiers généaraux pour le projet 7 d'openclassrooms

Yandex Practicum Data Science project

Building and leveraging a LGBM model to predict whether a mushroom is edible or poisonous

This is my Hamoye Stage C tag-along project. The notebook focuses on applying Machine Learning Classification models and Measuring Classification Performance.

Predicted the lithology of the formation using different algorithm

Predicting the stability of electrical grids using a binary classification model.