BestHub
Sign in
Data Party THU
Data Party THU
Jan 29, 2026 · Big Data

How a Tsinghua Big Data Program Turned a Chemistry PhD into an AI‑Powered Process Engineer

This article recounts a Tsinghua University PhD student's journey through a multidisciplinary big‑data training program, detailing the acquisition of AI and data‑science skills, the creation of novel algorithms like MicroFlowSAM and ImageRAG, and their successful application to chemical engineering research and industry projects.

Big DataChemical EngineeringIndustrial Application
0 likes · 8 min read
How a Tsinghua Big Data Program Turned a Chemistry PhD into an AI‑Powered Process Engineer
NewBeeNLP
NewBeeNLP
Jun 20, 2024 · Artificial Intelligence

How LLMs Transform Recommendation Systems: Insights from Kuaishou’s LERAN Paper

This article analyzes Kuaishou’s May 2024 paper on LLM‑driven recommendation, detailing its dual‑tower architecture, contrastive learning of user and item embeddings, and a CVR‑auxiliary task that together improve cold‑start handling and boost both offline and online AUC metrics.

Industrial ApplicationItem EmbeddingLLM
0 likes · 10 min read
How LLMs Transform Recommendation Systems: Insights from Kuaishou’s LERAN Paper
21CTO
21CTO
Oct 16, 2015 · Artificial Intelligence

Mastering Industrial Machine Learning: From Problem Modeling to Model Optimization

This article outlines a complete industrial machine‑learning workflow—starting with problem modeling, through data preparation, feature extraction, model training, and ending with model optimization—illustrated with a real‑world DEAL revenue‑prediction case and practical tips for handling data, features, and model selection.

Industrial Applicationdata preparationfeature engineering
0 likes · 20 min read
Mastering Industrial Machine Learning: From Problem Modeling to Model Optimization
Meituan Technology Team
Meituan Technology Team
Feb 10, 2015 · Artificial Intelligence

Practical Guide to Machine Learning at Meituan: From Problem Modeling to Model Optimization

This guide walks through Meituan’s end‑to‑end offline ML workflow—from problem modeling and data preparation, through feature engineering and normalization, to model selection, training optimization, evaluation, and iterative improvement—emphasizing business alignment, data quality, and practical diagnostics for real‑world deployment.

Industrial Applicationfeature engineeringmodel training
0 likes · 16 min read
Practical Guide to Machine Learning at Meituan: From Problem Modeling to Model Optimization