Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Concord Reviews & Ratings
    237 Ratings
    Company Website
  • RunPod Reviews & Ratings
    211 Ratings
    Company Website
  • SKU Science Reviews & Ratings
    16 Ratings
    Company Website
  • BrandMap® 10 Reviews & Ratings
    Company Website
  • TinyPNG Reviews & Ratings
    58 Ratings
    Company Website
  • optivalue.ai Reviews & Ratings
    4 Ratings
    Company Website
  • RaimaDB Reviews & Ratings
    12 Ratings
    Company Website
  • AnalyticsCreator Reviews & Ratings
    46 Ratings
    Company Website
  • dbt Reviews & Ratings
    259 Ratings
    Company Website
  • Fraud.net Reviews & Ratings
    56 Ratings
    Company Website

What is TabFM?

TabFM is a cutting-edge foundation model designed for zero-shot learning specifically tailored to manage tabular data, with the goal of simplifying the processes of classification and regression that often demand considerable manual training, hyperparameter tuning, and customized feature engineering. By reframing the difficulties associated with tabular prediction as an in-context learning challenge, TabFM eliminates the necessity of training a distinct supervised model for each dataset; rather, it merges previous training examples with target testing rows into a unified prompt, enabling it to identify the complex relationships that exist between different columns and rows during the inference phase. Since tables are fundamentally two-dimensional and do not depend on a predetermined order, TabFM utilizes a hybrid architecture that combines alternating attention mechanisms for both rows and columns, along with row compression methods, and a dedicated Transformer designed for in-context learning based on these compressed row representations. This advanced structure allows the model to adeptly capture intricate interactions and dependencies among features while ensuring computational efficiency, which is particularly beneficial for dealing with larger datasets. Moreover, this innovative methodology not only boosts performance but also markedly decreases the time and resources generally required for the development of models in tabular data applications, paving the way for more effective analytical solutions. As a result, TabFM represents a significant advancement in the realm of machine learning for tabular data, starting a new era in data analysis.

What is Amundsen?

Unlock the potential of your data by fostering confidence for more impactful analysis and modeling. By breaking down barriers between information silos, you can significantly boost productivity. Instantly access insights into your data while also observing how your colleagues are utilizing it. Enjoy a seamless search experience for data within your organization using an intuitive text-based interface. The search functionality leverages an algorithm similar to PageRank, allowing for personalized recommendations based on various factors such as names, descriptions, tags, and user interactions with tables and dashboards. Build trust in your data by depending on automated, curated metadata, which offers comprehensive details about tables and columns, insights on frequent users, timestamps of the latest updates, relevant statistics, and, when allowed, previews of the data. Improve data management efficiency by establishing connections to the ETL jobs and code that create the datasets. Provide clear definitions for table and column descriptions to reduce unnecessary debates about which data to use and the meanings of individual columns. Identify which datasets are most frequently accessed, owned, or bookmarked by your peers, thereby enhancing collaboration. Furthermore, gain insights into popular queries linked to a specific table by examining dashboards created from that dataset, which enhances your analytical capabilities. Ultimately, this holistic strategy ensures that your data-driven choices are informed and anchored in trustworthy information, leading to more effective outcomes.

Media

Media

Integrations Supported

AWS Glue
Amazon Athena
Amazon Redshift
Amazon Web Services (AWS)
Apache Cassandra
Apache Druid
Apache Hive
Apache Spark
Datafold
Delta Lake
Elasticsearch
Google Cloud BigQuery
Google Cloud Platform
IBM Db2
MySQL
Oracle Cloud Infrastructure
PostgreSQL
SQL Server
Snowflake
Vertica

Integrations Supported

AWS Glue
Amazon Athena
Amazon Redshift
Amazon Web Services (AWS)
Apache Cassandra
Apache Druid
Apache Hive
Apache Spark
Datafold
Delta Lake
Elasticsearch
Google Cloud BigQuery
Google Cloud Platform
IBM Db2
MySQL
Oracle Cloud Infrastructure
PostgreSQL
SQL Server
Snowflake
Vertica

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

research.google/blog/introducing-tabfm-a-zero-shot-foundation-model-for-tabular-data/

Company Facts

Organization Name

Amundsen

Company Location

United States

Company Website

www.amundsen.io

Categories and Features

Categories and Features

Popular Alternatives

MLBox Reviews & Ratings

MLBox

Axel ARONIO DE ROMBLAY

Popular Alternatives