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Performance Hints for BigQuery
trmlabs.com·8h·
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🚀Query Optimization
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Natural language processing for word sense disambiguation and information extraction
arxiv.org·19h·
Discuss: r/compsci
📥Feed Aggregation
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Navigating the Labyrinth: Effective Database Indexing Strategies
dev.to·2d·
Discuss: DEV
📇Indexing Strategies
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Self-Supervised Temporal Pattern Mining for circular manufacturing supply chains with embodied agent feedback loops
dev.to·6h·
Discuss: DEV
🌊Stream Processing
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Department of Computer Science and Technology – Technical reports: UCAM-CL-TR-949
cl.cam.ac.uk·6h·
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🔩Systems Programming
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Treating Functions as Vectors in Hilbert Space
hackaday.com·2d
📐Linear Algebra
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faradayio/xsv2: Fork of xsv because qsv is too much
github.com·12h·
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🗜️LZSS Variants
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Why MAP and MRR Fail for Search Ranking (and What to Use Instead)
towardsdatascience.com·2d
📊Search Ranking
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Running Code and Failing Models – Rajiv Shah
projects.rajivshah.com·2d
🧠Machine Learning
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Federation Over Embeddings: Let AI Agents Query Data Where It Lives
gnanaguru.com·2h·
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🏺Database Archaeology
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Climate Monitoring Search Engine: Multi-Vectors in Qdrant
pub.towardsai.net
·4d
🗂️Vector Search
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Measuring True Campaign Uplift in Noisy E-Commerce Data: A Practical Heuristic Approach
hackernoon.com·1d
📊Feed Optimization
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Pandas vs Polars: Why the 2025 Evolution Changes Everything
dev.to·12h·
Discuss: DEV
🌀Brotli Internals
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Information, Physics, and Computation (Oxford Graduate Texts): Mézard, Marc, Montanari, Andrea: 8601410201722: Amazon.com: Books
amazon.com·1d
📐Compression Mathematics
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What I Learned Building a Storage Engine That Outperforms RocksDB
tidesdb.com·5h·
Discuss: Hacker News, r/programming
🦀Rusty Databases
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Soft Filtering: Guiding Zero-shot Composed Image Retrieval with Prescriptive and Proscriptive Constraints
arxiv.org·2d
🧮Vector Embeddings
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Pokémon Team Optimization
nchagnet.pages.dev·2d·
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📈Linear programming
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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
🧭Content Discovery
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Rethinking data in NL2SQL: a survey of what we have and what we expect | Vicinagearth
link.springer.com·4d
📋Document Grammar
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timescale/pgvectorscale: Postgres extension for vector search (DiskANN), complements pgvector for performance and scale. Postgres OSS licensed.
github.com·3d·
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🧬PostgreSQL Forensics
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