Smart Data Collective

APRIL 13, 2021

In the modern world of business, data is one of the most important resources for any organization trying to thrive. Business data is highly valuable for cybercriminals. They even go after meta data. Big data can reveal trade secrets, financial information, as well as passwords or access keys to crucial enterprise resources.

Testing 122

Testing Behavioral Analytics Data-driven Big Data 122

IBM Big Data Hub

SEPTEMBER 20, 2022

And no, it’s not because the Giants and IBM are both nicknamed “Big Blue.” Back in 2016, IBM formed a partnership with ESPN. In this relationship, we use IBM’s advanced analytics and AI capabilities to analyze the massive amount of data produced by fantasy football. Let me explain.

Broadcasting 52

Broadcasting Statistics Consulting Data-driven 52

DataRobot Blog

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. Recently, Stanford University released its 2022 AI Index Annual Report , where it showed between 2016 and 2021, the number of bills containing artificial intelligence grew from 1 to 18 in 25 countries.

Risk 111

Risk Modeling IT Risk Management 111

Occam's Razor

MARCH 30, 2017

While the phrase Artificial Intelligence has been around since the first human wondered if she could go further if she had access to entities with inorganic intelligence, it truly jumped the shark in 2016. trillion pictures in 2016. One key thing that stymied my efforts, and likely your ML efforts, in 2016 was Identity.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

Domino Data Lab

AUGUST 8, 2019

Having participated in several Foo Camps—and even co-chaired the Ed Foo series in 2016-17— most definitely, a Foo will turn your head around. Putting discussions about security aside, the statistics competency required to confront fairness and bias issues for machine learning models in production set quite a high bar. machine learning?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

datapine

NOVEMBER 19, 2019

Currently, popular approaches include statistical methods, computational intelligence, and traditional symbolic AI. Some more examples of AI applications can be found in various domains: in 2020 we will experience more AI in combination with big data in healthcare. One of the IT buzzwords you must take note of in 2020.

Technology 279

Technology Internet of Things IT IoT 279

Rita Sallam

JULY 22, 2016

Gartner revamped the BI and Analytics Magic Quadrant in 2016 to reflect the mainstreaming of this market disruption. Not sure about that, but Sisense is well suited for easily harmonizing, combining and modeling many different, complex and large data sets for fast interactive analysis.

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

The Unofficial Google Data Science Blog

MARCH 31, 2016

Far from hypothetical, we have encountered these issues in our experiences with "big data" prediction problems. We often use statistical models to summarize the variation in our data, and random effects models are well suited for this — they are a form of ANOVA after all. arXiv preprint arXiv:1602.00047, (2016). [8]

Modeling 40

Modeling Statistics Advertising Testing 40

Occam's Razor

JULY 13, 2017

This is the simple view that greets you, outbreaks from 1890 to 2016 with vaccine development during that same time…. For each bar, click on Measles, you’ll see the first big outbreak (1917, 3,000 deaths) and the last (1989, 123 deaths). publishes a ton of data. And how can we do it better? Each element is clickable.

Visualization 124

Visualization Strategy Interactive Statistics 124