IBM Big Data Hub

NOVEMBER 15, 2017

Machine learning concerns in Silicon Valley tend to be different from those elsewhere in the U.S. — and outside of the U.S. So, here are five tips for those hearing about machine learning efforts in Silicon Valley, but who work elsewhere. These suggestions consider where machine learning and data science are headed on a large scale — as opposed to the fascinating (but often narrow) research happening in Silicon Valley.

Machine Learning 89

Machine Learning Data Science 89

Bruno Aziza

NOVEMBER 15, 2017

VEDA — Verizon Enterprise Data Analytics—is an enterprise organization that addresses data management, data governance, data warehousing and data lakes and common analytical and AI technologies.

Big Data 71

Big Data Data Lake Data Governance Enterprise 71

Smarten

NOVEMBER 14, 2017

Leave it to the Software! Predictive Analytics for the Faint of Heart! Assisted Predictive Modeling , Predictive Analytics. Those terms strike terror in the hearts of most business users, and that is understandable. These mysterious-sounding terms sound complicated and lead business users to imagine confounding, confusing algorithms, and endless strings of numbers.

Predictive Analytics 64

Predictive Analytics Analytics Predictive Modeling Forecasting 64

Perceptual Edge

NOVEMBER 13, 2017

One of the most popular shows in the early years of television was hosted by Art Linkletter, which included a segment called “Kids say the darndest things.” Linkletter would have conversations with young children who could be counted on to say things that adults found entertaining. I’ve experienced my own version of this in recent years that could be described as “Researchers say the darndest things.

Recreation/Entertainment 55

Recreation/Entertainment Visualization Statistics Publishing 55

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m

Testing

IBM Big Data Hub

NOVEMBER 17, 2017

Organizations everywhere, from massive governments to the smallest start-ups, are in a race for the best-possible data expertise and tools. To help your team understand the data science journey, IBM created the Data Science for All webcast.

Data Science 84

Data Science IT 84

Bruno Aziza

NOVEMBER 15, 2017

Three days of thought-provoking discussion and stimulating ideas about the impacts of Big Data, AI, Robotics and Innovation.

Big Data 57

Big Data 57

Nutanix

NOVEMBER 14, 2017

State and local government organizations in the U.S. face daunting IT challenges as they look to improve service delivery while controlling costs. Key obstacles they face are a reliance on older IT systems, lack of skilled employees and inadequate budgets.

IT 20

IT 20

IBM Big Data Hub

NOVEMBER 17, 2017

Long before humans go to the moon or Mars, we'll need to send unmanned missions to establish the early infrastructure. Don Haderle, a scholar of the mainframe, recently suggested that mainframe computer systems will become the obvious solution for the moon, Mars, and beyond. Learn why.

75

75

Bruno Aziza

NOVEMBER 16, 2017

Data rules the world, but who rules the data? The companies that collect it? The servers that store it? The cables and satellites that transmit it? Or the laws that keep it flowing into the right hands—and away from the wrong ones? Welcome to the world of data governance.

Data Governance 56

Data Governance IT 56

Cloudera

NOVEMBER 13, 2017

As the market moves toward cloud-based big data and analytics, three qualities emerge as vital for success. While many services will get some traction without meeting all three goals, they will also disappoint users and cause perpetual headaches for IT. At Cloudera, we see these undisputable attributes to be: Easy – Certainly no one goes out looking for a harder way to do their job.

Analytics 40

Analytics Big Data Machine Learning Cost-Benefit 40

Advertisement

The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.

Strategy

IBM Big Data Hub

NOVEMBER 13, 2017

In most modern-day organizations, external macros tend to be very influential — leaving little bandwidth for optimizing data governance. And, as stricter data storage and security compliance regulations come into play, it's becoming more and more critical for organizations to ensure they have the right data and that it's properly stored and managed, both for compliance and insights.

Data Governance 54

Data Governance Interactive Optimization Management 54

IBM Big Data Hub

NOVEMBER 16, 2017

Information analytics has never been a “one size fits all” proposition. That applies to the hardware and software technologies organizations employ, the information being parsed and the goals of specific projects.

Machine Learning 46

Machine Learning Analytics Software Technology 46

Cloudera

NOVEMBER 15, 2017

What’s more terrifying, knowing that you just lost your identity or unknowingly being manipulated? While they both seem awful, they are the reality of the digital world that we live in, just look at the news. With countless articles discussing the recent Equifax hack where thousands of social security numbers were compromised to organizations like Facebook, Google, and Twitter coming forward with Russian accounts that were buying ads to influence US elections.

Behavioral Analytics 41

Behavioral Analytics Risk Analytics Management 41