playcanvas/engine
github.com·8h
🎮gaming
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The Three Ages of Data Science: When to Use Traditional Machine Learning, Deep Learning, or an LLM (Explained with One Example)
towardsdatascience.com·1d
🔄Data Engineering
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Keynote: Turn Up the Heat: Driving Cloud Native Innovation into Real-World Impact- Multiple Speakers
youtube.com·14h
📡Event-Driven Architecture
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Quantification and object perception in Multimodal Large Language Models deviate from human linguistic cognition
arxiv.org·1d
✅Pydantic
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Enhancing Decentralized Prediction Market Accuracy via Bayesian Federated Learning with Adaptive Trust Weights
🔬Synthetic Data
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AI-Powered Data Visualization Platform: An Intelligent Web Application for Automated Dataset Analysis
arxiv.org·1d
📓Jupyter Notebooks
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Adaptive Gradient-Free Optimization via High-Dimensional Feature Space Mapping & Ensemble Learning
🔄Data Engineering
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🔥 LLM Interview Series(1): What Are Large Language Models and How Do They Work
🎀Decorators
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Correcting False Alarms from Unseen: Adapting Graph Anomaly Detectors at Test Time
arxiv.org·2d
🐻❄️Polars
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FaithAct: Faithfulness Planning and Acting in MLLMs
arxiv.org·1d
🔬Synthetic Data
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GastroDL-Fusion: A Dual-Modal Deep Learning Framework Integrating Protein-Ligand Complexes and Gene Sequences for Gastrointestinal Disease Drug Discovery
arxiv.org·2d
🐻❄️Polars
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Hybrid Autoencoders for Tabular Data: Leveraging Model-Based Augmentation in Low-Label Settings
arxiv.org·2d
🔄Data Engineering
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Model Counting for Dependency Quantified Boolean Formulas
arxiv.org·2d
🔁Itertools
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