AWS Machine Learning Blog

FEBRUARY 13, 2024

Let’s demystify this using the following personas and a real-world analogy: Data and ML engineers (owners and producers) – They lay the groundwork by feeding data into the feature store Data scientists (consumers) – They extract and utilize this data to craft their models Data engineers serve as architects sketching the initial blueprint.

ML 105

ML ML Engineer Machine Learning Data Scientist 105

AWS Machine Learning Blog

MARCH 30, 2023

This allows for seamless communication of positional data and various outputs of Bundesliga Match Facts between containers in real time. The match-related data is collected and ingested using DFL’s DataHub. Both the Lambda function and the Fargate container publish the data for further consumption in the relevant MSK topics.

Machine Learning 72

Machine Learning Data Scientist Metadata Data Science 72

AWS Machine Learning Blog

FEBRUARY 28, 2024

Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. The solution in this post aims to bring enterprise analytics operations to the next level by shortening the path to your data using natural language. Today, generative AI can enable people without SQL knowledge.

Metadata 111

Metadata LLM Generative AI NLP 111

AWS Machine Learning Blog

OCTOBER 20, 2023

Data scientists search and pull features from the central feature store catalog, build models through experiments, and select the best model for promotion. Data scientists create and share new features into the central feature store catalog for reuse.

ML 101

ML Data Scientist ML Engineer Data Science 101

The MLOps Blog

JUNE 27, 2023

Databricks Databricks is a cloud-native platform for big data processing, machine learning, and analytics built using the Data Lakehouse architecture. When thinking about a tool for metadata storage and management, you should consider: General business-related items : Pricing model, security, and support.

Machine Learning 134

Machine Learning Metadata Data Quality Data Scientist 134

Snorkel AI

JULY 5, 2023

We thought we’d structure this more as a conversation where we walk you through some of our thinking around some of the most common themes in data centricity in applied AI. Is more data always better? And the important thing here is really the predictive signal in the data. Maybe I’ll start us off here Robert?

Large Language Models 52

Large Language Models Metadata AI AI 52

Snorkel AI

JULY 5, 2023

We thought we’d structure this more as a conversation where we walk you through some of our thinking around some of the most common themes in data centricity in applied AI. Is more data always better? And the important thing here is really the predictive signal in the data. Maybe I’ll start us off here Robert?

Large Language Models 52

Large Language Models Metadata AI AI 52