Google MeridianGoogle
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NVIDIA PhysicsNeMoNVIDIA
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About
Google Meridian is an open source Marketing Mix Modeling (MMM) framework built by Google to help advertisers and analysts accurately measure the impact of their marketing efforts across online and offline channels without relying on cookies or user-level tracking. At its core, Meridian uses a Bayesian causal-inference model that can ingest aggregated data (spend, sales or KPI outcomes, reach/frequency, geo-level data, seasonality, and external controls) to estimate the incremental contribution each marketing channel (e.g., search, social, video, offline media) makes to overall performance, and compute return on ad spend (ROAS), response curves, and optimal budget allocation. Because it’s open source, users have full transparency into methodology and code, giving them control over model configuration, data inputs, and assumptions.
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About
NVIDIA PhysicsNeMo is an open source Python deep-learning framework for building, training, fine-tuning, and inferring physics-AI models that combine physics knowledge with data to accelerate simulations, create high-fidelity surrogate models, and enable near-real-time predictions across domains such as computational fluid dynamics, structural mechanics, electromagnetics, weather and climate, and digital twin applications. It provides scalable, GPU-accelerated tools and Python APIs built on PyTorch and released under the Apache 2.0 license, offering curated model architectures including physics-informed neural networks, neural operators, graph neural networks, and generative AI–based approaches so developers can harness physics-driven causality alongside observed data for engineering-grade modeling. PhysicsNeMo includes end-to-end training pipelines from geometry ingestion to differential equations, reference application recipes to jump-start workflows.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
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Audience
Marketing teams, data scientists, and analysts seeking a tool to build robust, transparent, privacy-compliant attribution models to understand real marketing impact, optimize budget allocation, and forecast ROI
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Audience
Researchers, engineers, and developers who need an open source Python AI framework to build, train, fine-tune, and deploy physics-informed machine learning models for simulation, digital twins, and real-time prediction
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationGoogle
Founded: 1998
United States
developers.google.com/meridian
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Company InformationNVIDIA
Founded: 1993
United States
developer.nvidia.com/physicsnemo
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