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py-why
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inferen…
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DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inferen…
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Uplift modeling and causal inference with machine learning algorithms
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High-performance data engine for AI and multimodal workloads. Process images, audio, video, and structured data at any scale
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comment engine
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A framework for efficient model inference with omni-modality models
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ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic de…
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A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
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Lightweight, fast, stable, programmable component-based rule engine — where AI Agents orchestrate just like ordinary components. Uniquely designed DSL: component reuse,…
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A unified inference and post-training framework for accelerated video generation.
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Achieve state of the art inference performance with modern accelerators on Kubernetes
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Vendor-agnostic orchestration for training, inference and agentic workloads across NVIDIA, AMD, TPU, and Tenstorrent on clouds, Kubernetes, and bare metal.
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A MySQL-compatible relational database with a storage agnostic query engine. Implemented in Go.