Remove Accountability Remove Analytics Remove Entertainment Remove Scripts
article thumbnail

­­Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

AWS Machine Learning

The offline store data is stored in an Amazon Simple Storage Service (Amazon S3) bucket in your AWS account. Apache Iceberg is an open table format for very large analytic datasets. To schedule the procedures, you set up an AWS Glue job using a Python shell script and create an AWS Glue job schedule. AWS Glue Job setup.

Scripts 73
article thumbnail

Is it time to reassess your QA function?

Tethr

Today, most companies are using some sort of speech analytics technology to handle QA, but is it enough? Script adherence Proper greeting Required closing Compliance (proper authentication, retrieval of account number, disclosure statement) Skills & behaviors (professionalism, empathy, subject matter expertise, confidence, friendliness).

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

25 Call Center Leaders Share the Most Effective Ways to Boost Contact Center Efficiency

Callminer

Bill Dettering is the CEO and Founder of Zingtree , a SaaS solution for building interactive decision trees and agent scripts for contact centers (and many other industries). Interactive agent scripts from Zingtree solve this problem. Agents can also send feedback directly to script authors to further improve processes.

article thumbnail

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

In addition to awareness, your teams should take action to account for generative AI in governance, assurance, and compliance validation practices. You should begin by extending your existing security, assurance, compliance, and development programs to account for generative AI.

article thumbnail

FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

article thumbnail

Power recommendations and search using an IMDb knowledge graph – Part 3

AWS Machine Learning

Many AWS media and entertainment customers license IMDb data through AWS Data Exchange to improve content discovery and increase customer engagement and retention. In this post, we illustrate how to handle OOC by utilizing the power of the IMDb dataset (the premier source of global entertainment metadata) and knowledge graphs.

article thumbnail

Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 2

AWS Machine Learning

Automating the client-server infrastructure to support multiple accounts or virtual private clouds (VPCs) requires VPC peering and efficient communication across VPCs and instances. The tables are de-identified to meet the regulatory requirements US Health Insurance Portability and Accountability Act (HIPAA).