ODSC - Open Data Science

SEPTEMBER 17, 2024

Bitter Lessons Learned While Building Production-quality RAG Systems for Professional Users of Academic Data Jeremy Miller | Product Manager, Academic AI Platform | Clarivate The gap between a RAG Demo and a Production-Quality RAG System remains stubbornly difficult to cross.

LLM 52

LLM Large Language Models Metadata Data Science 52

ODSC - Open Data Science

JULY 26, 2024

Streamlining Unstructured Data for Retrieval Augmented Generatio n Matt Robinson | Open Source Tech Lead | Unstructured Learn about the complexities of handling unstructured data, and practical strategies for extracting usable text and metadata from it. You’ll also discuss loading processed data into destination storage.

Data Scientist 52

Data Scientist Robotics Metadata Data Science 52

Snorkel AI

JANUARY 24, 2023

Labeled data can be loaded back into Snowflake as structured data. Data ingestion sources in Snorkel Flow, now includes Snowflake Data Cloud Organizations also have the option of deploying complex ML models on Snowflake. Schedule a custom demo tailored to your use case with our ML experts today.

Data Ingestion 52

Data Ingestion Machine Learning Data Science ML 52

Snorkel AI

JANUARY 24, 2023

Labeled data can be loaded back into Snowflake as structured data. Data ingestion sources in Snorkel Flow, now includes Snowflake Data Cloud Organizations also have the option of deploying complex ML models on Snowflake. Schedule a custom demo tailored to your use case with our ML experts today.

Data Ingestion 52

Data Ingestion Machine Learning Data Science ML 52

The MLOps Blog

FEBRUARY 13, 2025

The solution lies in systems that can handle high-throughput data ingestion while providing accurate, real-time insights. Some teams try to cope by batching or sampling metrics, but these approaches sacrifice real-time visibility and add complexity to the code. Tools like neptune.ai

Data Ingestion 59

Data Ingestion Automation Software Engineer Metadata 59

The MLOps Blog

DECEMBER 12, 2024

See the docs or watch a short product demo (2 min) Play with a live Neptune Scale project Request your early access What does this mean for enterprise teams? Related Strategies For Effective Prompt Engineering Read more The future: what were building next At Neptune, weve nailed the data ingestion partits fast, reliable, and efficient.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models LLM 52

TensorFlow

JANUARY 18, 2023

The first part is all about the core TFX pipeline handling all the steps from data ingestion to model deployment. We built a simple yet complete ML pipeline with support for automatic data ingestion, data preprocessing, model training, model evaluation, and model deployment in TFX. Hub service.

Data Ingestion 52

Data Ingestion ML DevOps Automation 52

DataRobot Blog

NOVEMBER 3, 2022

Flexible BigQuery Data Ingestion to Fuel Time Series Forecasting. Request a demo. To understand how DataRobot AI Cloud and Big Query can align, let’s explore how DataRobot AI Cloud Time Series capabilities help enterprises with three specific areas: segmented modeling, clustering, and explainability.

Data Scientist 52

Data Scientist Explainability Black Box AI Automation 52

The MLOps Blog

JUNE 27, 2023

Core features of end-to-end MLOps platforms End-to-end MLOps platforms combine a wide range of essential capabilities and tools, which should include: Data management and preprocessing : Provide capabilities for data ingestion, storage, and preprocessing, allowing you to efficiently manage and prepare data for training and evaluation.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

The MLOps Blog

MAY 9, 2023

The components comprise implementations of the manual workflow process you engage in for automatable steps, including: Data ingestion (extraction and versioning). Data validation (writing tests to check for data quality). Data preprocessing. This demo uses Arrikto MiniKF v20210428.0.1 CSV, Parquet, etc.)

ML 98

ML Machine Learning Metadata Data Science 98

AWS Machine Learning Blog

OCTOBER 23, 2024

Boost productivity – Empowers knowledge workers with the ability to automatically and reliably summarize reports and articles, quickly find answers, and extract valuable insights from unstructured data. The following demo shows Agent Creator in action.

Generative AI 74

Generative AI IDP LLM Automation 74

The MLOps Blog

MARCH 21, 2023

An ML platform standardizes the technology stack for your data team around best practices to reduce incidental complexities with machine learning and better enable teams across projects and workflows. We ask this during product demos, user and support calls, and on our MLOps LIVE podcast. Why are you building an ML platform?

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69