AWS Machine Learning

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

Best practices 124

Best practices Government Engineering Accountability 124

DMG Consulting

AUGUST 17, 2017

Companies are striving to understand customer needs, engage Millennial customers and employees, increase the use of self-service tools, improve service quality while reducing costs, simplify operating environments, and reduce fraud, and they’re looking to vendors for help. Self-service. Customer journey analytics.

Contact Center 69

Contact Center Technology Big data Gamification 69

REVE Chat Blog

FEBRUARY 12, 2020

Chatbots in banking gives those who prefer self-service a way to talk to their bank as a person and to have a conversation, even when requesting information. In-app chatbots can access user account details and provide completely personalized information and help or even financial advice based on data. .

Banking 76

Banking Customer Experience Chatbots Big data 76

AWS Machine Learning

OCTOBER 20, 2023

Governing ML lifecycle at scale is a framework to help you build an ML platform with embedded security and governance controls based on industry best practices and enterprise standards. Data scientists create and share new features into the central feature store catalog for reuse.

Government 103

Government Engineering Accountability Enterprise 103

AWS Machine Learning

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. Data scientists and ML engineers require capable tooling and sufficient compute for their work. JuMa is now available to all data scientists, ML engineers, and data analysts at BMW Group.

Engineering 73

Engineering Analytics Government Self service 73

ConvergeOne

DECEMBER 7, 2021

The underlying technologies of composability include some combination of artificial intelligence (AI), machine learning, automation, container-based architecture, big data, analytics, low-code and no-code development, Agile/DevOps deployment, cloud delivery, and applications with open APIs (microservices).

APIs 90

APIs Big data Analytics Engineering 90

Xaqt

JUNE 22, 2020

Despite significant advancements in big data and open source tools, niche Contact Center Business Intelligence providers are still wed to their own proprietary tools leaving them saddled with technical debt and an inability to innovate from within. Together, we can develop best practices and sharable templates for the entire industry.

Call Center 52

Call Center Contact Center Analytics Engineering 52