TildAlice – Tech Blog for Developers
Python, AI, Deep Learning, Data Analysis, Computer Vision, Reinforcement Learning โ tips and tutorials
Latest Posts
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Advanced Claude Code: Multi-Agent Workflows and Skills
Multi-agent pipelines in Claude Code solve the 200K token context wall. Here's how to chain agents without losing state or burning tokens.
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Claude Code: AI-Powered Dev in Your Terminal
Claude Code runs AI in your terminal with full filesystem access. After 3 months in production: what breaks, what scales, what's worth it.
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GAN์ผ๋ก ์๋ ๊ณ ์ฅ ๋ฐ์ดํฐ ์ฆ๊ฐํ๊ธฐ: CWRU ๋ฒ ์ด๋ง ๋ฐ์ดํฐ์ ์ด์ ํ์ง ์ ํ๋ ๊ฐ์ ์คํ
GAN data augmentation boosted bearing fault detection accuracy from 72% to 89% on CWRU dataset. Here's the exact preprocessing pipeline.
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Pandas DataFrame ์๋ฒฝ ๊ฐ์ด๋: ๋ฐ์ดํฐ ๋ถ์ ๊ธฐ์ด๋ถํฐ ์ค๋ฌด ํ์ฉ๊น์ง
Pandas DataFrame operations that actually matter: merge strategies, groupby pitfalls, and memory optimization tricks for 100M+ row datasets.
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MARL ์ค์ ๊ฐ์ด๋: QMIX, MAPPO, MADDPG ๊ตฌํ ๋น๊ต
QMIX vs MAPPO vs MADDPG on cooperative tasks: which multi-agent RL algorithm converges faster? Benchmarks from 10M training steps.
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LoRA vs QLoRA vs DoRA ์๋ฒฝ ๋น๊ต: ํ๋ผ๋ฏธํฐ ํจ์จ์ ํ์ธํ๋(PEFT) ๋ฉ๋ชจ๋ฆฌ ์ต์ ํ ์ค์ ๊ฐ์ด๋
LoRA uses 60GB GPU, QLoRA needs 16GB, DoRA hits 12GB โ same model quality. Here's the memory breakdown and when to pick each method.
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Ruff vs Black vs isort: 2026๋ Python ํฌ๋งคํฐ ์ฑ๋ฅ ๋ฒค์น๋งํฌ์ ๋ง์ด๊ทธ๋ ์ด์ ๊ฐ์ด๋
Ruff formats 100K Python files in 0.8s. Black takes 47s, isort takes 23s. Migration guide included โ no config changes needed.
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LSTM vs Transformer RUL ์์ธก: NASA CMAPSS ์คํ ๋น๊ต
Transformer beat LSTM by 18% RMSE on NASA turbofan RUL prediction. Attention maps reveal why โ and when LSTM still wins.