Popular GitHub Repositories for Model Training And Evaluation

This repository contains a project showcasing Federated Learning using the EMNIST dataset. Federated Learning is a privacy-preserving machine learning approach that allows a model to be trained across multiple decentralized devices or servers holding local data samples, without exchanging them.

This project aims to build a machine learning pipeline that predicts customer churn using AWS services like SageMaker for model training and deployment, along with Docker for containerization.

using YOLOv7 for shoe detection and ResNet for shoe classification

Successfully established a supervised machine learning model which can accurately forecast the total weekly sales amount obtained at Walmart stores, based on a certain set of features provided as input.

Successfully developed a machine learning model which can accurately classify the weather based on various features pertaining to weather-related data and atmospheric conditions.

AutoML-MLOps is a comprehensive platform that simplifies the machine learning workflow by automating model development, training, and deployment. With features like real-time dashboards, interactive data visualization, and automated target selection, it enables both beginners and experienced data scientists to save time and improve model accuracy.

Explore advanced neural networks for crafting captivating headlines! Compare LSTM ? and Transformer ? models through interactive notebooks ? and easy-to-use wrapper classes ??. Ideal for content creators and data enthusiasts aiming to automate and enhance headline generation ?.

Successfully established a supervised machine learning model which can predict the quality of a wine to a high level of accuracy based on a certain set of features associated with the chemical properties and characteristics of that specific wine.

Developing explainable multimodal AI models with hands-on lab on the life-cycle of rare event prediction in manufacturing @ AAAI-25

Deployment ready machine learning model to predict the math scores of students based on various features related to their demographics, background, and academic engagement.

Successfully developed a machine learning model which can accurately predict the strength of cement based on various features such as blast furnace slag, water, coarse aggregate, etc.

This repository contains a Loan Approval Prediction Model. The model predicts the likelihood of loan approval based on applicant data. The model deployment is done using FastAPI to allow applicant data to be entered in order to obtain an approval prediction.

Successfully established a machine learning model that can accurately classify an e-commerce product into one of four categories, namely "Books", "Clothing & Accessories", "Household" and "Electronics", based on the product's description.

一套完整的工具包，用于训练、评估和部署 SPLADE 模型

A no-boilerplate, ease-to-use AI/ML experiment tracker.

Successfully established a supervised machine learning model which can accurately predict the gross sales generated by an XYZ company based on its weekly spends on distinct marketing channels across a span of 4 years from 2015 to 2019.

这个项目利用机器学习流水线，根据用户的个人信息预测保险费用。项目包含数据导入、预处理、模型训练以及通过Flask API进行预测服务。应用还使用MLflow记录预测结果和实验细节。