Remove Metadata Remove Modeling Remove Publishing
article thumbnail

Build Write-Audit-Publish pattern with Apache Iceberg branching and AWS Glue Data Quality

AWS Big Data

The importance of publishing only high-quality data cant be overstatedits the foundation for accurate analytics, reliable machine learning (ML) models, and sound decision-making. We discuss two common strategies to verify the quality of published data. The metadata of an Iceberg table stores a history of snapshots.

article thumbnail

Underlying Engineering Behind Alexa’s Contextual ASR

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Conventionally, an automatic speech recognition (ASR) system leverages a single statistical language model to rectify ambiguities, regardless of context. However, we can improve the system’s accuracy by leveraging contextual information.

Metadata 400
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Neptune.ai?—?A Metadata Store for MLOps

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. A centralized location for research and production teams to govern models and experiments by storing metadata throughout the ML model lifecycle. A Metadata Store for MLOps appeared first on Analytics Vidhya. Keeping track of […].

Metadata 143
article thumbnail

Proposals for model vulnerability and security

O'Reilly on Data

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks. This is like a denial-of-service (DOS) attack on your model itself.

Modeling 278
article thumbnail

The state of data quality in 2020

O'Reilly on Data

Just 20% of organizations publish data provenance and data lineage. These include the basics, such as metadata creation and management, data provenance, data lineage, and other essentials. They’re still struggling with the basics: tagging and labeling data, creating (and managing) metadata, managing unstructured data, etc.

article thumbnail

The New O’Reilly Answers: The R in “RAG” Stands for “Royalties”

O'Reilly on Data

Will content creators and publishers on the open web ever be directly credited and fairly compensated for their works’ contributions to AI platforms? Generative AI models are trained on large repositories of information and media. Will there be an ability to consent to their participation in such a system in the first place?

Metadata 293
article thumbnail

How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

EUROGATEs data science team aims to create machine learning models that integrate key data sources from various AWS accounts, allowing for training and deployment across different container terminals. From here, the metadata is published to Amazon DataZone by using AWS Glue Data Catalog.

IoT 107