Auto-complete Data Drift LLM 
ODSC - Open Data Science
OCTOBER 11, 2023
Machine learning models are only as good as the data they are trained on. Even with the most advanced neural network architectures, if the training data is flawed, the model will suffer. Data issues like label errors, outliers, duplicates, data drift, and low-quality examples significantly hamper model performance.
The MLOps Blog
JUNE 27, 2023
Can you see the complete model lineage with data/models/experiments used downstream? Amazon SageMaker Ground Truth SageMaker Ground Truth is a fully managed data labeling service designed to help you efficiently label and annotate your training data with high-quality annotations. Can you render audio/video?
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
The MLOps Blog
MARCH 12, 2024
TL;DR LLMOps involves managing the entire lifecycle of Large Language Models (LLMs), including data and prompt management, model fine-tuning and evaluation, pipeline orchestration, and LLM deployment. Prompt-response management: Refining LLM-backed applications through continuous prompt-response optimization and quality control.
Topbots
JUNE 29, 2023
On a more advanced stance, everyone who has done SQL query optimisation will know that many roads lead to the same result, and semantically equivalent queries might have completely different syntax. The manual collection of training data for Text2SQL is particularly tedious.
AWS Machine Learning Blog
DECEMBER 4, 2024
SageMaker AI makes sure that sensitive data stays completely within each customer’s SageMaker environment and will never be shared with a third party. Deepchecks Deepchecks specializes in LLM evaluation. This proactive approach allows teams to quickly resolve issues, continuously improving model reliability and performance.
Expert insights. Personalized for you.
52 
Let's personalize your content