Crash Course to Crack Machine Learning Interview – Part 2: Linear Regression
analyticsvidhya.com·1d
🤖Machine Learning
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Social and UGC: The trust engines powering search everywhere
searchengineland.com·3d
🌲B-Trees
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AI Agents Observability with OpenTelemetry and the VictoriaMetrics Stack
victoriametrics.com·1d
👁️Observability
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Which Chip Is Best?
⭕Consistent Hashing
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No AI in Agents
💬Natural Language Processing
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The Complexity Cliff: Why Reasoning Models Work Right Up Until They Don't
⚖️CAP Theorem
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“Write Smarter, Not Harder: Unleashing the Potential of AI Writing Tools”
pub.towardsai.net·1d
💬Natural Language Processing
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Human-centric photo dataset aims to help spot AI biases responsibly
techxplore.com·2d
🤖Machine Learning
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Path-Coordinated Continual Learning with Neural Tangent Kernel-Justified Plasticity: A Theoretical Framework with Near State-of-the-Art Performance
arxiv.org·3d
💬Natural Language Processing
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<p>**Abstract:** This paper introduces the Automated Policy Impact Assessment and Strategic Recommendation Engine (APISRE), a novel system leveraging multi-moda...
freederia.com·1d
💬Natural Language Processing
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Systematic Evaluation of Preprocessing Techniques for Accurate Image Registration in Digital Pathology
arxiv.org·1d
🤖Machine Learning
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SAIL-RL: Guiding MLLMs in When and How to Think via Dual-Reward RL Tuning
arxiv.org·3d
♟Chess Programming
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Redundancy Maximization as a Principle of Associative Memory Learning
arxiv.org·3d
🤖Machine Learning
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A brief guide for those who slept (on AI) the last two years
💬Natural Language Processing
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Fleming-VL: Towards Universal Medical Visual Reasoning with Multimodal LLMs
arxiv.org·4d
🤖Machine Learning
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Automated Optimization of Single-Molecule Magnet (SMM) Anisotropy via Machine Learning-Guided Ligand Design
🎯Bitboards
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