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Global Concert Ticket Price Prediction System: An End-to-End Machine Learning Solution Based on XGBoost
This article introduces a complete intelligent concert ticket price prediction system, which combines the XGBoost, Scikit-learn, and Streamlit tech stack to implement an end-to-end machine learning application from data exploration to interactive dashboards.
信用评分多分类预测：基于Random Forest和CatBoost的机器学习方案
本文介绍一个信用评分多分类项目，使用Random Forest和CatBoost算法构建预测模型，将客户划分为不同的信用等级。
AI Cyber Shield: Artificial Intelligence Cybersecurity Protection Knowledge Base
This article introduces the AI Cyber Shield project, an open knowledge base for artificial intelligence cybersecurity protection, covering AI security architecture, defense frameworks, protection technologies, and analysis notes.
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RLMedNAS: Reinforcement Learning-Driven Automated Neural Architecture Search for Medical Imaging
This article introduces the RLMedNAS project, which uses reinforcement learning to automate neural architecture search in the field of medical imaging, addressing the issues of low efficiency and suboptimal structure in traditional manual design.
Dental AI Evaluation Benchmark: A Large Language Model Evaluation Dataset for Medical Scenarios
This article introduces the Dental AI Evaluation Benchmark project, a professionally designed dataset for medical scenarios, which is used to systematically evaluate the instruction-following ability, factual accuracy, and answer quality of large language models.
Audit Copilot: An AI Intelligent Assistant Platform for Audit and Finance
This article introduces the Audit Copilot project, a comprehensive AI platform built with FastAPI and React, integrating RAG, OCR, and large language model technologies to provide intelligent solutions for audit, accounting, tax, and fraud detection.
Intelligent E-commerce Analysis and Prediction System Based on the Olist Dataset
Using Python, NLP, and machine learning technologies to conduct in-depth analysis and predictive modeling on data from Brazil's Olist e-commerce platform, covering order analysis, comment sentiment analysis, and sales prediction.
BioPredictor v3.6: A Browser-Based Platform for Drug-Protein Interaction Analysis and 3D Visualization
A browser-based bioinformatics application that combines machine learning, binding affinity prediction, and 3D target visualization to provide practical tools for drug screening and early bioinformatics evaluation.
Intent Preservation Benchmark: Evaluating Large Language Models' Ability to Preserve Human Intent in High-Risk Scenarios
An open-source evaluation framework designed to measure whether large language models faithfully preserve humans' original intent during complex information transformation processes, with a special focus on high-risk fields such as healthcare.
AI 2048 Coach: A Neural Network System for Real-Time Guidance of iPhone 2048 via Screen Mirroring
An innovative AI game coaching system that captures the iPhone screen via AirPlay mirroring, recognizes the 2048 game board in real time, and uses a self-learned n-tuple neural network to provide optimal sliding suggestions for each step within 45 milliseconds.
MLLM-Shap: Implementing Shapley Value Explanation Method for Multimodal Large Language Models
A bachelor's project in Data Science at Warsaw University of Technology extends the traditional Shapley value explanation method to multimodal large language models, supporting interpretability analysis for text and audio models.
NeuralLinearSolve.jl: A Neural Network-Enhanced Linear System Solver
A Julia package from the SciML ecosystem that uses neural network technology to accelerate and enhance traditional linear solvers, providing a new solution paradigm for large-scale scientific computing.
BaddieVision: An Intelligent Badminton Video Analysis System Based on Computer Vision
BaddieVision is a complete badminton video analysis toolchain that integrates MediaPipe pose estimation, TrackNetV3 shuttlecock tracking, YOLO object detection, and LSTM temporal classification technologies to enable end-to-end automated analysis from raw video to tactical insights.
MediLens-AI: An Intelligent Medical Assistant System Integrating RAG Technology
MediLens-AI is a comprehensive AI medical assistant that combines machine learning-based disease prediction, Gemini-powered medical report analysis, and an RAG-driven intelligent Q&A system. It demonstrates how to safely integrate large language models with medical data, providing a technical reference for personalized health consultation.
ConnectFourAI: An Intelligent Connect Four Game Engine Based on Adversarial Search
ConnectFourAI is a modular Connect Four game engine that fully implements an AI system ranging from basic game rules to advanced adversarial search algorithms. The project includes random agents, rule-based agents, and Minimax agents with Alpha-Beta pruning, making it an excellent teaching case for understanding game tree search and competitive AI design.
SentriAI: Large Language Model Security Assessment and Threat Intelligence Platform
SentriAI is a comprehensive platform focused on large language model (LLM) security assessment, integrating threat intelligence, behavior analysis, MITRE ATLAS framework mapping, and compliance monitoring functions to provide all-round support for AI security research.
WODanalytics: A CrossFit Training Analysis Platform Based on Django and Machine Learning
A comprehensive training management platform integrating Django REST Framework, Docker containerization, and machine learning prediction models, designed specifically for CrossFit and hybrid training.
AI Engineering Lab: Generative AI and RAG Practical Project Collection
A collection of practical projects showcasing generative AI, RAG pipelines, AI agents, and LLM applications. Each project can run independently and is accompanied by complete documentation.
CrowdDNA: A Crowd Risk Prediction System Based on Graph Neural Networks and Computer Vision
An intelligent analysis platform that uses YOLOv8, ByteTrack, Graph Attention Network (GAT), and GRU temporal models to perform real-time risk classification on crowd videos.
ReX-CoDA: A Machine Learning Imputation Framework for Left-Censored Geochemical Composition Data
ReX-CoDA is a model-agnostic iterative framework specifically designed to handle the common left-censorship problem in geochemical data. It combines machine learning prediction with Mills ratio truncated normal correction to perform composition-aware missing value imputation in the additive log-ratio space.
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