IBM Data Science in Practice

DECEMBER 7, 2022

Next Generation DataStage on Cloud Pak for Data Ensuring high-quality data A crucial aspect of downstream consumption is data quality. Studies have shown that 80% of time is spent on data preparation and cleansing, leaving only 20% of time for data analytics.

Data Quality 130

Data Quality Data Pipeline Data Preparation ETL 130

Snorkel AI

DECEMBER 2, 2024

At its core, Snorkel Flow empowers data scientists and domain experts to encode their knowledge into labeling functions, which are then used to generate high-quality training datasets. This approach not only enhances the efficiency of data preparation but also improves the accuracy and relevance of AI models.

AWS 52

AWS Machine Learning Machine Learning Data Preparation 52

IBM Data Science in Practice

NOVEMBER 28, 2022

Ensuring high-quality data A crucial aspect of downstream consumption is data quality. Studies have shown that 80% of time is spent on data preparation and cleansing, leaving only 20% of time for data analytics. This leaves more time for data analysis.

Data Pipeline 130

Data Pipeline Data Quality Data Preparation Data Governance 130

Snorkel AI

NOVEMBER 9, 2023

LLM distillation will become a much more common and important practice for data science teams in 2024, according to a poll of attendees at Snorkel AI’s 2023 Enterprise LLM Virtual Summit. As data science teams reorient around the enduring value of small, deployable models, they’re also learning how LLMs can accelerate data labeling.

Data Science 59

Data Science Data Scientist Data Preparation AI 59

Snorkel AI

NOVEMBER 9, 2023

LLM distillation will become a much more common and important practice for data science teams in 2024, according to a poll of attendees at Snorkel AI’s 2023 Enterprise LLM Virtual Summit. As data science teams reorient around the enduring value of small, deployable models, they’re also learning how LLMs can accelerate data labeling.

Data Science 52

Data Science Data Scientist Data Preparation AI 52

Towards AI

DECEMBER 19, 2024

Last Updated on December 20, 2024 by Editorial Team Author(s): Towards AI Editorial Team Originally published on Towards AI. Data preparation using Roboflow, model loading and configuration PaliGemma2 (including optional LoRA/QLoRA), and data loader creation are explained.

Database 104

Database AI AI Data Preparation 104

AWS Machine Learning Blog

FEBRUARY 18, 2025

The following sections further explain the main components of the solution: ETL pipelines to transform the log data, agentic RAG implementation, and the chat application. Creating ETL pipelines to transform log data Preparing your data to provide quality results is the first step in an AI project.

AWS 78

AWS Database ETL AI 78