📝 NLP

Natural Language Processing, Text Analysis, Language Models, Document Processing

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TRUNAJOD: A text complexity library for text analysis built on spaCy — TRUNAJOD 0.1.1 documentation
trunajod20.readthedocs.io·9h
🔧DSPy
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The Transformer Architecture: A Deep Dive into How LLMs Actually Work
dev.to·4h·
Discuss: DEV
📖Digital Hermeneutics
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How to Deconstruct Almost Anything My Postmodern Adventure
fudco.com·3h·
Discuss: Hacker News
🚀Science Fiction
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vagos/llm-grep: Match lines using both classic and semantic regular expressions with LLM.
github.com·1d·
Discuss: Lobsters
🔤Text Processing
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[Discussion] The "Noise" Bottleneck in Local 8B RAG – A comparison of cleaning strategies (Regex vs. Unstructured vs. Entropy)
reddit.com·5h·
Discuss: r/LocalLLaMA
🌸Bloom Filters
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The 2025 Guide to Machine Learning
ibm.com·1d·
Discuss: Hacker News
📱Edge AI
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TOON for LLMs: A Comparative Performance Analysis against JSON
gist.github.com·8h·
Discuss: DEV
💬Prompt Engineering
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The Case for Snake Case: A Kolmogorov Complexity Argument
modulovalue.com·1d·
Discuss: Hacker News
🔧DSPy
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kalolad1/llm-sorter: A Python library that uses LLMs as comparators for semantic sorting. Sort any list by meaning, tone, complexity, urgency, or any criteria expressible in natural language.
github.com·8h·
Discuss: Hacker News
💸Affordable LLMs
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A Review of Language Machines by Leif Weatherby
deontologistics.substack.com·1d·
Discuss: Substack
📖Digital Hermeneutics
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Docling + Go + Bob: The Modern Document Stack
dev.to·1d·
Discuss: DEV
🔤Text Processing
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Introducing the XLab AI Security Guide
lesswrong.com·7h
🛡️AI Security
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Going back to go forwards and instruction design<!-- -->
lukes-blog.vercel.app·1h·
Discuss: Hacker News
💬Prompt Engineering
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Prompts are becoming Code, but we still treat them like Strings
dev.to·16h·
Discuss: DEV
💬Prompt Engineering
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Getting to know Claude better
future.forem.com·18h·
Discuss: DEV
💬AI Code Assistants
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Engineer1999/A-Curated-List-of-ML-System-Design-Case-Studies: This repository contains a curated collection of 300+ case studies from over 80 companies, detailing practical applications and insights into machine learning (ML) system design. The contents are organized to help you easily find relevant case studies based on industry or specific ML use cases.
github.com·4d
🔄Feed Processing
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Tackling Unmaintainable Complexity with Automation: Building a Multi-Tenant SaaS Solo
ko-chan.github.io·8h·
Discuss: DEV
📋Infrastructure as Code (IaC)
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Interviewing for ML/AI Engineers
moderndescartes.com·1d·
Discuss: Hacker News
💬Prompt Engineering
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Role of NLP Testing in Test Automation and AI-Driven QA
dev.to·3d·
Discuss: DEV
🧪Test Automation
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I made a CLI to train LLMs in 2 commands (no PyTorch boilerplate)
github.com·2d·
Discuss: r/LocalLLaMA
💬Prompt Engineering
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