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. billion in 2017 to $190.61 billion by 2025. Blockchain.

Technology 279

Technology Internet of Things IT IoT 279

Smart Data Collective

MARCH 27, 2020

Statistics show that married people have fewer car accidents than singletons. Insurance companies have access to crime statistics and can track the number of car theft and break-ins per neighborhood. Marital status. The assumption is that married people tend to drive more carefully with children in the car.

Insurance 137

Insurance Measurement Risk Cost-Benefit 137

BizAcuity

APRIL 28, 2019

is delinquent as of June 30th, 2017. Today, it’s no secret that most forward-thinking businesses are keenly following the latest developments on big data, artificial intelligence, machine learning, and predictive analytics. And this data is crucial in taking the necessary steps to ensure successful debt collection.

Predictive Analytics 98

Predictive Analytics Analytics Big Data Data mining 98

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. In 2017, additional regulation targeted much smaller financial institutions in the U.S. The FDIC’s action was announced through a Financial Institution Letter, FIL-22-2017.

Risk 111

Risk Modeling IT Risk Management 111

AWS Big Data

AUGUST 9, 2024

Amazon Redshift at Dafiti Amazon Redshift is a fully managed data warehouse service, and was adopted by Dafiti in 2017. large nodes and with the launch of Redshift Spectrum and the migration of our cold data to the data lake, then we considerably improved our architecture and migrated to four dc2.8xlarge nodes.

Data Lake 111

Data Lake Analytics Data Warehouse Data-driven 111

Cloudera

SEPTEMBER 10, 2021

The IRS has spent more than a decade working to combat high-cost hazards, including launching a collaborative Identity Theft Tax Refund Fraud Information Sharing and Analysis Center (ISAC) pilot for the 2017 tax-filing season, advancing authentication tools and taking proactive steps in fighting business identity theft.

Machine Learning 69

Machine Learning Statistics Data-driven Big Data 69

Peter James Thomas

APRIL 9, 2019

As in 2017 , I have failed miserably in my original objective of posting this early in January. Overall the total number of articles and new pages I published exceeded 2017’s figures to claim the second spot behind 2009; our first year in business. These are as follows: General Data Articles. Data Visualisation.

Data-driven 49

Data-driven Statistics Data Science Big Data 49

Sisense

JANUARY 14, 2021

However, the methods they had at their disposal initially couldn’t keep up with their growing user base and the ever-evolving world of big data. Michael Hartmann, VP of Business Intelligence With a Master of Science in physics, Michael has been working in data analysis and fintech since 2014.

Dashboards 85

Dashboards Testing Business Intelligence Interactive 85

IBM Big Data Hub

JUNE 21, 2023

And this year, Wimbledon is tapping into the power of generative AI, producing new digital experiences on the Wimbledon app and website using IBM’s new trusted AI and data platform, watsonx.

Consulting 69

Consulting Unstructured Data Digital Transformation Statistics 69

The Unofficial Google Data Science Blog

JULY 22, 2020

For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. One reason to do ramp-up is to mitigate the risk of never before seen arms.

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

Domino Data Lab

AUGUST 8, 2019

Another key point: troubleshooting edge cases for models in production—which is often where ethics and data meet, as far as regulators are concerned—requires much more sophistication in statistics than most data science teams tend to have. It’s a quick way to clear the room. machine learning?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Peter James Thomas

JUNE 20, 2019

Of course it can be argued that you can use statistics (and Google Trends in particular) to prove anything [1] , but I found the above figures striking. © Scott Adams (2017) – dilbert.com. In 2017, a survey estimated that 68 percent of American offices had low or no separation between workers. Source: Google Trends.

Cost-Benefit 55

Cost-Benefit Data Warehouse Data Science Consulting 55

Peter James Thomas

AUGUST 12, 2018

I explore some similar themes in a section of Data Visualisation – A Scientific Treatment. Integrity of statistical estimates based on Data. Having spent 18 years working in various parts of the Insurance industry, statistical estimates being part of the standard set of metrics is pretty familiar to me [7].

Metrics 49

Metrics Statistics Data Quality Measurement 49

Smart Data Collective

AUGUST 5, 2020

Specifically, they apply the examination of historical crime statistics and face-recognition technology to improve staff effectiveness. As a rule, predictive algorithms and other AI systems that are based on machine learning apply already existing historical data sets. It depends strictly on the type and quality of data received.

Risk 136

Risk Statistics Machine Learning Big Data 136

Domino Data Lab

MAY 8, 2019

Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Adrian Weller (2017-07-29). “ They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Challenges for Transparency ”. Riccardo Guidotti, et al.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

O'Reilly on Data

JANUARY 25, 2021

Our data shows that Chef and Puppet peaked in 2017, when Kubernetes started an almost exponential growth spurt, as Figure 4 shows. AI, Machine Learning, and Data. Healthy growth in artificial intelligence has continued: machine learning is up 14%, while AI is up 64%; data science is up 16%, and statistics is up 47%.

Machine Learning 364

Machine Learning Software Testing Technology 364

Occam's Razor

JULY 13, 2017

As an analyst, as a Big Data person, as a Data Scientist, pouring the right data on humanity is only marginally effective. Consider this, conversion rate could go up by a statistically significant percentage… While revenue actually goes down. publishes a ton of data. Insanely helpful. 17 mil lives saved.

Visualization 125

Visualization Strategy Interactive Statistics 125