Xebia
AUGUST 9, 2023
Table of Contents What is Machine Learning System Design? Design Process Clarify requirements Frame problem as an ML task Identify data sources and their availability Model development Serve predictions Observability Iterate on your design What is Machine Learning System Design?
Apiumhub
JULY 16, 2023
In their thought-provoking presentation titled “Pragmatic Approach to Architecture Metrics” at GSAS’22 organized by Apiumhub , Sonya Natanzon, and Vlad Khononov delivered valuable insights. Consequently, we assess the capacity of architecture to embrace change through various metrics. Whatever that is.”
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Tenable
NOVEMBER 25, 2022
Get the latest on the Hive RaaS threat; the importance of metrics and risk analysis; cloud security’s top threats; supply chain security advice for software buyers; and more! . But to truly map cybersecurity efforts to business objectives, you’ll need what CompTIA calls “an organizational risk approach to metrics.”.
Honeycomb
APRIL 29, 2024
s favorite three buzzwords (logs, metrics, and traces), we can draw several analogies to understand software development and debugging. The real vs. simulated systems In Baudrillard’s terms, the authentic experiences and the real have been replaced by symbols and signs ( logs , metrics , traces ).
John Snow Labs
NOVEMBER 9, 2023
Furthermore, we’ll perform robustness testing for Large Language Models and evaluate them using various evaluation metrics, including Embedding Distance Metrics, String Distance Metrics, and QAEvalChain approach inspired by the LangChain library. Consider a QA system designed to provide medical advice.
Cloudera
DECEMBER 3, 2021
They identified four main categories: capturing intent, system design, human judgement & oversight, regulations. An AI system trained on data has no context outside of that data. Designers therefore need to explicitly and carefully construct a representation of the intent motivating the design of the system.
AWS Machine Learning - AI
APRIL 3, 2024
Search engines and recommendation systems powered by generative AI can improve the product search experience exponentially by understanding natural language queries and returning more accurate results. Amazon OpenSearch Service now supports the cosine similarity metric for k-NN indexes.
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