ODSC - Open Data Science

APRIL 28, 2023

Be sure to check out her talk, “ Power trusted AI/ML Outcomes with Data Integrity ,” there! Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation.

ML 98

ML ML Data Silos Data Quality 98

AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at any single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

AWS 107

AWS Analytics Analytics Machine Learning 107

AWS Machine Learning Blog

MARCH 15, 2024

Many organizations are implementing machine learning (ML) to enhance their business decision-making through automation and the use of large distributed datasets. With increased access to data, ML has the potential to provide unparalleled business insights and opportunities. In such scenarios, you can use FedML Octopus.

AWS 140

AWS ML ML Machine Learning 140

Becoming Human

MARCH 16, 2023

Machine Learning Machine learning (ML) focuses on training computer algorithms to learn from data and improve their performance, without being explicitly programmed. ML solutions encompass a diverse array of branches, each with its own unique characteristics and methodologies.

AI 139

AI AI Deep Learning Deep Learning 139

AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

AWS 102

AWS Analytics Analytics Machine Learning 102

DrivenData Labs

MARCH 30, 2023

His interests are in privacy-preserving machine learning, particularly in the areas of differential privacy, ML security, and federated learning. Mayank Shah is a Data Science Consultant at ZS and holds a Bachelor’s in Technology for Computer Science from Maharaja Agrasen Institute of Technology.

Machine Learning 162

Machine Learning Machine Learning Data Science Algorithm 162

AWS Machine Learning Blog

SEPTEMBER 14, 2023

The following risks and limitations are associated with LLM based queries that a RAG approach with Amazon Kendra addresses: Hallucinations and traceability – LLMS are trained on large data sets and generate responses on probabilities. This can lead to inaccurate answers, which are known as hallucinations.

AWS 130

AWS AI AI Data Silos 130