📄 文章列表
141 篇文章
TDS
Conceptual Frameworks for Data Science Projects
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Scaling Recommender Transformers to a Billion Parameters
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Deep Reinforcement Learning: 0 to 100
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From Classical Models to AI: Forecasting Humidity for Energy and Water Efficiency in Data Centers
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What to Do When Your Credit Risk Model Works Today, but Breaks Six Months Later
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The Reinforcement Learning Handbook: A Guide to Foundational Questions
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Introducing ShaTS: A Shapley-Based Method for Time-Series Models
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Do Labels Make AI Blind? Self-Supervision Solves the Age-Old Binding Problem
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Deep Reinforcement Learning: The Actor-Critic Method
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Beyond Prompting: The Power of Context Engineering
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From RGB to Lab: Addressing Color Artifacts in AI Image Compositing
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Time Series Isn’t Enough: How Graph Neural Networks Change Demand Forecasting
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Evaluating Multi-Step LLM-Generated Content: Why Customer Journeys Require Structural Metrics
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Air for Tomorrow: Mapping the Digital Air-Quality Landscape, from Repositories and Data Types to Starter Code
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Causal ML for the Aspiring Data Scientist
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From Connections to Meaning: Why Heterogeneous Graph Transformers (HGT) Change Demand Forecasting
TDS
Modeling Urban Walking Risk Using Spatial-Temporal Machine Learning
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On the Possibility of Small Networks for Physics-Informed Learning
TDS
Distributed Reinforcement Learning for Scalable High-Performance Policy Optimization
TDS