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Introduction to lakehouse architecture
The lakehouse architecture bridges the gap between data lakes and warehouses, providing unified governance, performance, and flexibility. This post introduces the core principles, benefits, and technologies behind lakehouses, explaining why theyâve become the foundation for modern data platforms in 2025.
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Topics Everyone Is Talking About No352
Rob Pike got spammed with an AI slop act of kindness ⢠Always bet on text ⢠How Lewis Carroll computed determinants ⢠How uv got so fast ⢠The Algebra of Loans in Rust
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Introduction to fairness in machine learning
Fairness in machine learning ensures that AI systems make equitable decisions across different groups. This beginner-friendly introduction covers key fairness definitions, sources of bias, core metrics, mitigation strategies, and the leading tools engineers use to build fair models.
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Empirical: LSTM vs Prophet vs ARIMA
This empirical deep dive compares LSTM, Prophet, and ARIMAâthree dominant paradigms in time series forecastingâacross accuracy, interpretability, and computational trade-offs. Drawing from post-2024 experiments, the post explores when each model shines, how they scale in production, and emerging hybrid trends for data scientists.
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Tools: abstract base classes and dataclasses for GRASP
Abstract Base Classes (ABCs) and dataclasses provide structural and conceptual clarity in Python applications. This post explores how these tools reinforce GRASP design principlesâlike low coupling, polymorphism, and information expertâoffering engineers practical patterns for building clean, maintainable, and scalable systems.
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