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Contains our Approach for the competition organized at Udyam'21
Objective is to develop a predictive model for a consumer finance company to identify potential loan defaulters. By analyzing historical loan data, & diff. data the factors that influences loan default rate.
Example notebooks to produce the models used in the SexEst web application.
Implémentation d'un modèle de scoring (OpenClassrooms | Data Scientist | Projet 7)
This project is about to detecting the text generated by different LLM given prompt. The instance is labeled by Human and Machine, and this project utilised both traditional machine learning method and deep learning method to classify the instance.
A machine learning based forecasting system for taxi demand prediction
This approach has the potential to create accurate, generalizable and adaptable machine learning methods that effectively and sustainably address agricultural tasks such as yield prediction and early disease identification.
Machine Learning model for heart failure prediction using LGBM Classifier.
Learning to Rank - Cross Sell
Early prediction of Mortality Risk among Covid -19 Patients in early stages when patients gets admitted into the hospital.
Spectral type classification using LGBM and deployed using FastAPI, Pydantic, and Docker
End to end Heart Diseases Prediction Model with webapp using Flask
Participated in Analytics Vidya Hackathon ( JOB-A-THON | May 2021 ). This Repository contains all code, reports and approach.
how to predict score credit to home credit indonesia with machine learning modeling, find more to Home Credit Indonesia
Predicting Next Booking Destinations for Airbnb Users. Feel free to access the Streamlit App in the link below.
Rank 4/125 MachineHack
The task is to predict whether a passenger was transported to an alternate dimension during the Spaceship Titanic's collision with the spacetime anomaly. To help us make these predictions, we are given a set of personal records recovered from the ship's damaged computer system.
The classification problem of student dropout data of an institute
Using LGBMClassifier to solve To-Be Challenge, which is a machine learning challenge on CodaLab Platform that aims to adress the problems of medical imbalanced data classification.
This repository contain my final projekt on the Data science Skillbox school on the topic: "Development of a machine learning algorithm to predict the behavior of customers of the "SberAvtopodpiska"
Music Genre Recommender website that can identify and recommend 10 different genres of music using Light Gradient Boosting Machine (LGBM). An accuracy of 90% was achieved on the test set by tuning the hyperparameters of the model with Optuna.
Déploiement d'une API Flask du modèle de classification déployée sur Heroku (OpenClassrooms | Data Scientist | Projet 7)
Various classification algorithms are implemented to predict whether a person is prone to or is suffering from heart disease.
Loan Eligibility - Classification (Python)
Predicted the lithology of the formation using different algorithm
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.
Yandex Practicum Data Science project
Practicum Workshop
Predicting the stability of electrical grids using a binary classification model.
Junky Union is creating a system to sort movie reviews. They aim to train a model to detect negative reviews using the IMBD dataset with polarity labeling. The model must classify reviews as positive or negative with an F1 score of at least 0.85.
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.
Kaggle Playground Series - Season 3, Episode 26 - Multi-Class Cirrhosis | EDA | MI-Score | Feature Engineering
Credit_Card_Approval_odinschool_project