Crash Course to Crack Machine Learning Interview – Part 2: Linear Regression
analyticsvidhya.com·1h
🤖Machine Learning
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An introduction to program synthesis (Part II) - Automatically generating features for machine learning
🤖Machine Learning
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DS-STAR: A state-of-the-art versatile data science agent
research.google·19h
📊Data Science
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Towards Humanist Superintelligence
🤖AI
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AI Turns Brain Scans Into Full Sentences and It’s Eerie To Say The Least
zmescience.com·22h
🤖AI
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Essential Chunking Techniques for Building Better LLM Applications
machinelearningmastery.com·1d
📈Optimization
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Plush neuron makes AI approachable, simplifies neural networks for middle schoolers
phys.org·12h
🤖AI
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Towards Transparent Stance Detection: A Zero-Shot Approach Using Implicit and Explicit Interpretability
arxiv.org·1d
🤖Machine Learning
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Structural Priors and Modular Adapters in the Composable Fine-Tuning Algorithm of Large-Scale Models
arxiv.org·8h
📈Optimization
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Hemorica: A Comprehensive CT Scan Dataset for Automated Brain Hemorrhage Classification, Segmentation, and Detection
arxiv.org·8h
👁️Computer Vision
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A Quantized VAE-MLP Botnet Detection Model: A Systematic Evaluation of Quantization-Aware Training and Post-Training Quantization Strategies
arxiv.org·1d
🤖Machine Learning
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Beyond Standard LLMs
🤖Machine Learning
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MoM: Mixtures of Scenario-Aware Document Memories for Retrieval-AugmentedGeneration Systems
🤖Machine Learning
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**Hyperlocal Weather Anomaly Forecasting via Spatiotemporal Graph Neural Networks & Ensemble Kalman Filtering**
🤖Machine Learning
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SSPO: Subsentence-level Policy Optimization
arxiv.org·8h
📈Optimization
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Generative Hints
arxiv.org·1d
🖼Image Processing
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The compute rethink: Scaling AI where data lives, at the edge
venturebeat.com·1d
🤖AI
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