Remove Metadata Remove Modeling Remove Publishing
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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
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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
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Specialized tools for machine learning development and model governance are becoming essential

O'Reilly on Data

A few years ago, we started publishing articles (see “Related resources” at the end of this post) on the challenges facing data teams as they start taking on more machine learning (ML) projects. We are still in the early days for tools supporting teams developing machine learning models. Model governance.

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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 275
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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.

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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 292
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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 101