There are 2 repositories under lightgbm-classifier topic.
The purpose of this project's design, development, and structure is to create an end-to-end Machine Learning Operations (MLOps) lifecycle to classify an individual's level of obesity based on their physical characteristics and eating habits.
A Data science app to predict who in Africa is most likely to have a bank account?
Helping Farmers make informed decisions with Machine Learning ! 👩🌾🚜
This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD).
This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD) with MRI data.
This repository contains code and data for analyzing real estate trends, predicting house prices, estimating time on the market, and building an interactive dashboard for visualization. It is structured to cater to data scientists, real estate analysts, and developers looking to understand property market dynamics.
Spam SMS Detection Project implemented using NLP & Transformers. DistilBERT - a hugging face Transformer model for text classification is used to fine-tune to best suit data to achieve the best results. Multinomial Naive Bayes achieved an F1 score of 0.94, the model was deployed on the Flask server. Application deployed in Google Cloud Platform
In this project we try to predict home credit default risk for clients. We try to predict, if the client will have payment difficulties or not.
Telco Churn Analysis and Modeling is a comprehensive project focused on understanding and predicting customer churn in the telecommunications industry. Utilizing advanced data analysis and machine learning techniques, this project aims to provide insights into customer behavior and help develop effective strategies for customer
A machine learning model to predict whether a customer will be interested to take up a credit card, based on the customer details and its relationship with the bank.
Maximizing Revenue with Individualized Coupon Optimization Using Tree-Based Models
Développer un modèle de scoring de la probabilité de défaut de paiement du client pour étayer la décision d'accorder ou non un prêt à un client potentiel.
The problem that this case study is dealing with predicts the location that a user is most likely to book for the first time. The accurate prediction helps to decrease the average time required to book by sharing more personalized recommendations and also in better forecasting of the demand. We use the browser’s session data as well as the user’s demographic information that is provided to us to create features that help in solving the problem.
The Aim of this project is used to identify whether a new transaction is fraudulent or not.
NLP Workshop -ML India
Machine Learning Model for predicting the estimated amount for renting a bicycle as a function of various parameters like the day of the week, wind speed, temperature, etc.
Example using Optuna to tune hyper parameters for LightGBM
FastAPI backend for CropFusionAI
Selected Paper from the AI-CyberSec 2021 Workshop in the 41st SGAI International Conference on Artificial Intelligence (MDPI Journal Electronics)
CS5228 Kaggle Inclass Competition: Predicting if Income > 50K
This project is aimed at predicting the case of customer's default payments. This dataset (30000,25) contains information on default payments, demographic factors, credit data, history of payment, and bill statements of credit card clients in Taiwan is used to build a classification model.
Anomaly Detection with Multiple Techniques using KDDCUP'99 Dataset
The goal of this project is to predict the expression on the face. The expression labels are standard ones used in psychology research: angry, disgusted, fearful, happy, sad, surprised, neutral.
Udacity DSND capstone project on the Bertelsmann-Arvato challenge on customer segmentation report and supervised learning model.
Projeto de Machine Learning baseado no Dataset Bank Marketing encontrado na UC Irvine - Machine Learning Repository e disponibilizado por S. Moro, R. Laureano e P. Cortez.
Accommodating supervised learning algorithms for the historical prices of the world's favorite cryptocurrency and boosting it through LightGBM.
Notes, tutorials, code snippets and templates focused on LightGBM for Machine Learning
This repository houses all files related to my second Springboard Capstone: Automated Tagging of Stack Exchange Data Science Posts Using Natural Language Processing.
Final Project Of Computational Intelligence - Fall 2021 - LightGBM, RandomForest and StackingClassifier
Conception and deployment of a credit-scoring model, API and interactive dashboard
The project aims to predict the 10-year risk of future coronary heart disease (CHD) for patients in Framingham, Massachusetts. A dataset (3390,16) containing demographic, behavioral, and medical risk factors of patients is used to build a classification model.
NTU SC1015 SC16 Team 2 Project
Photometric light curves classification with machine learning
Banking fraudulent transaction detection using machine learning models.
Machine learning project to predict obesity risk levels based on lifestyle and demographic data. This project utilizes advanced algorithms like CatBoost, LightGBM, and more to classify individuals into different obesity categories