Google MeridianGoogle
|
||||||
Related Products
|
||||||
About
Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. For example, in an application that recommends a music playlist, features could include song ratings, listening duration, and listener demographics. Features are used repeatedly by multiple teams and feature quality is critical to ensure a highly accurate model. Also, when features used to train models offline in batch are made available for real-time inference, it’s hard to keep the two feature stores synchronized. SageMaker Feature Store provides a secured and unified store for feature use across the ML lifecycle. Store, share, and manage ML model features for training and inference to promote feature reuse across ML applications. Ingest features from any data source including streaming and batch such as application logs, service logs, clickstreams, sensors, etc.
|
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.
|
|||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||||
Audience
Enterprises seeking a solution to store, share, and manage ML model features for training
|
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
|
|||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||||
API
Offers API
|
API
Offers API
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
No information available.
Free Version
Free Trial
|
Pricing
Free
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationAmazon
Founded: 1994
United States
aws.amazon.com/sagemaker/feature-store/
|
Company InformationGoogle
Founded: 1998
United States
developers.google.com/meridian
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
|
|
||||||
|
|
||||||
Categories |
Categories |
|||||
Integrations
AWS Glue
AWS Lake Formation
Amazon Athena
Amazon Kinesis
Amazon Redshift
Amazon S3
Amazon SageMaker
Amazon SageMaker Data Wrangler
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
|
Integrations
AWS Glue
AWS Lake Formation
Amazon Athena
Amazon Kinesis
Amazon Redshift
Amazon S3
Amazon SageMaker
Amazon SageMaker Data Wrangler
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
|
|||||
|
|
|