Snorkel AI

OCTOBER 4, 2023

FMs can even transform dense tabular data into digestible consumer profiles. Data scientists can train large language models (LLMs) and generative AI like GPT-3.5 to generate natural language reports from tabular data that help human agents easily interpret complex data profiles on potential borrowers.

AI 64

AI AI ML ML 64

Alation

DECEMBER 7, 2021

As a platform for data intelligence , Alation boasts open APIs with which Bigeye can easily integrate. This integration empowers all data consumers, from business users, to stewards, analysts, and data scientists, to access trustworthy and reliable data.

Data Quality 52

Data Quality Data Pipeline Data Observability Data Profiling 52

Snorkel AI

OCTOBER 4, 2023

FMs can even transform dense tabular data into digestible consumer profiles. Data scientists can train large language models (LLMs) and generative AI like GPT-3.5 to generate natural language reports from tabular data that help human agents easily interpret complex data profiles on potential borrowers.

AI 59

AI AI ML ML 59

Snorkel AI

OCTOBER 4, 2023

FMs can even transform dense tabular data into digestible consumer profiles. Data scientists can train large language models (LLMs) and generative AI like GPT-3.5 to generate natural language reports from tabular data that help human agents easily interpret complex data profiles on potential borrowers.

AI 52

AI AI ML ML 52

Dataconomy

FEBRUARY 23, 2023

They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. This involves working closely with data analysts and data scientists to ensure that data is stored, processed, and analyzed efficiently to derive insights that inform decision-making.

Big Data 91

Big Data Big Data Data Engineering Data Engineer 91

Alation

MAY 24, 2022

Prime examples of this in the data catalog include: Trust Flags — Allow the data community to endorse, warn, and deprecate data to signal whether data can or can’t be used. Data Profiling — Statistics such as min, max, mean, and null can be applied to certain columns to understand its shape.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

Iguazio

FEBRUARY 17, 2024

How can financial services companies build, expand and optimize their use of data and ML? Open and free financial datasets and economic datasets are an essential starting point for data scientists and engineers who are developing and training ML models for finance. But sadly, they can be hard to come by. Get the datasets here.

Machine Learning 40

Machine Learning Machine Learning ML ML 40

Snorkel AI

MAY 12, 2023

My name is Erin Babinski and I’m a data scientist at Capital One, and I’m speaking today with my colleagues Bayan and Kishore. We’re here to talk to you all about data-centric AI. Publishing standards for data and governance of that data is either missing or very widely far from an ideal.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Snorkel AI

MAY 12, 2023

My name is Erin Babinski and I’m a data scientist at Capital One, and I’m speaking today with my colleagues Bayan and Kishore. We’re here to talk to you all about data-centric AI. Publishing standards for data and governance of that data is either missing or very widely far from an ideal.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

AWS Machine Learning Blog

APRIL 18, 2023

The sample set of de-identified, already publicly shared data included thousands of anonymized user profiles, with more than fifty user-metadata points, but many had inconsistent or missing meta-data/profile information. Matthew Rhodes is a Data Scientist working in the Amazon ML Solutions Lab.

AWS 87

AWS Machine Learning Machine Learning ML 87

The MLOps Blog

MAY 17, 2023

ETL pipeline | Source: Author These activities involve extracting data from one system, transforming it, and then processing it into another target system where it can be stored and managed. ML heavily relies on ETL pipelines as the accuracy and effectiveness of a model are directly impacted by the quality of the training data.

ETL 59

ETL Data Pipeline ML ML 59

DagsHub

AUGUST 23, 2024

Data quality is crucial across various domains within an organization. For example, software engineers focus on operational accuracy and efficiency, while data scientists require clean data for training machine learning models. Without high-quality data, even the most advanced models can't deliver value.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Pickl AI

OCTOBER 11, 2023

Key Features Benefit from the real-time surveillance thus, it helps in identifying potential issues in real-time It comes with advanced analytical capacities contributing to well-informed decision-making; Intuitively explore and grasp the intricacies of data.

Data Observability 52

Data Observability Data Quality Data Pipeline Data Governance 52