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Shapley Values are one of the most common methods for explainability, yet they can be…
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Latest
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The 2026 Goal Tracker: How I Built a Data-Driven Vision Board Using Python, Streamlit, and Neon
ProductivityDesigning a centralized system to track daily habits and long-term goals
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Why speed without standards creates fragile AI products
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From optimizing metrics to designing meaning: putting people back into data-driven decisions
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How structured knowledge became healthcare’s quiet advantage
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A history of Transformer artifacts and the latest research on how to fix them
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Topic Modeling Techniques for 2026: Seeded Modeling, LLM Integration, and Data Summaries
Machine LearningSeeded topic modeling, integration with LLMs, and training on summarized data are the fresh parts…
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The how, why, what and where of Amazon’s LLM access layer
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Dataflows were (rightly?) considered “the slowest and least performant option” for ingesting data into Power…
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Longer summers, milder winters: analysis of temperature trends in Uzès, France, year after year.
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Editor’s Picks
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Learn how to get the most out of agentic coding
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The eternal promise of self-service analytics
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Looking at the performance of different pipelines
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Understanding the foundations of federated learning
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Achieving infinite context with 114× less memory
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Why Retrieval Helps in Time Series Forecasting We all know how it goes: Time-series data…
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Apply the best methods from academia to get the most out of practical applications
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Part 2: Avoiding burnout, learning strategies and the superpower of solitude
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Instead of using shift as an excuse for poor performance, use Inverse Probability Weighting to…
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The Variable Newsletter
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Don’t miss our most popular articles of the previous month
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Essential reads on how to boost your current skill set and plan for career growth…
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Deep Dives
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A deep dive on data transfer bottlenecks, their identification, and their resolution with the help…
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Walkthrough using open-source prompt optimization algorithms in Python to improve the accuracy of an autonomous…
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Hands-on walkthroughs of problems and solution approaches that power real‑world data science use cases
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Using ACE to create self-improving LLM workflows and structured playbooks
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How approximate vector search silently degrades Recall—and what to do about It
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A practical guide to observability, evaluations, and model comparisons
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