IBM Big Data Hub

APRIL 18, 2024

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. It might analyze real-time data from cameras, LiDAR and other sensors to identify objects, assess risks and anticipate environmental changes like sudden weather events or unexpected obstacles.

Cost-Benefit 89

Cost-Benefit Manufacturing Modeling Interactive 89

The Unofficial Google Data Science Blog

JULY 22, 2020

One reason to do ramp-up is to mitigate the risk of never before seen arms. 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.

Experimentation 95

Experimentation Statistics Testing Knowledge Discovery 95

The Unofficial Google Data Science Blog

JUNE 30, 2016

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. Identification We now discuss formally the statistical problem of causal inference. We start by describing the problem using standard statistical notation.

Statistics 44

Statistics Optimization Modeling Experimentation 44

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Now, there is a data risk here.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

O'Reilly on Data

MARCH 23, 2023

What is it, how does it work, what can it do, and what are the risks of using it? Tokens ChatGPT’s sense of “context”—the amount of text that it considers when it’s in conversation—is measured in “tokens,” which are also used for billing. And it can look up an author and make statistical observations about their interests.

IT 270

IT Modeling Testing Risk 270

Domino Data Lab

MAY 8, 2019

That’s a risk in case, say, legislators – who don’t understand the nuances of machine learning – attempt to define a single meaning of the word interpret. Visualizations are vital in data science work, with the caveat that the information that they convey may be 4-5 layers of abstraction away from the actual business process being measured.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

The Unofficial Google Data Science Blog

MAY 31, 2016

It is important that we can measure the effect of these offline conversions as well. Panel studies make it possible to measure user behavior along with the exposure to ads and other online elements. Let's take a look at larger groups of individuals whose aggregate behavior we can measure. days or weeks).

Advertising 42

Advertising Testing Sales Statistics 42

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. These measurement-obsessed companies have an advantage when it comes to AI.

Management 110

Management Machine Learning Experimentation Metrics 110

O'Reilly on Data

DECEMBER 9, 2019

We develop an ordinary least squares (OLS) linear regression model of equity returns using Statsmodels, a Python statistical package, to illustrate these three error types. CI theory was developed around 1937 by Jerzy Neyman, a mathematician and one of the principal architects of modern statistics.

Statistics 27

Statistics Uncertainty Risk Marketing 27

Occam's Razor

JANUARY 9, 2012

Most companies are astonishingly blasé about data and possibilities of measurement. " Sad, unimaginative measurements of their sad, unimaginative campaigns. We don't take risk and try things, imaginative (possibly glorious) things, because we believe the price of failure is so high. AND you can control for risk!

Marketing 142

Marketing B2B Measurement Risk 142

Occam's Razor

MARCH 23, 2010

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. Yet case studies in some sense reduced risk, even if they were simply over blown marketing fluff written by the vendor. Part of it fueled by some Consultants.

Analytics 119

Analytics Consulting Metrics Experimentation 119

Cloudera

NOVEMBER 25, 2020

And soon also sensor measures, and possibly video or audio data with the increased use of device technology and telemedicine in medical care. How can he make it easy to see statistics, and do calculations, on discovered commonalities, across structured and unstructured data?

Data Warehouse 60

Data Warehouse Unstructured Data Analytics Visualization 60

Domino Data Lab

AUGUST 26, 2019

To support the iterative and experimental nature of industry work, Domino reached out to Addison-Wesley Professional (AWP) for appropriate permissions to excerpt the “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. Beyond this, we also get a measure of the variability.

Testing 79

Testing Modeling Machine Learning Metrics 79

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

1]" Statistics, as a discipline, was largely developed in a small data world. More people than ever are using statistical analysis packages and dashboards, explicitly or more often implicitly, to develop and test hypotheses. Data was expensive to gather, and therefore decisions to collect data were generally well-considered.

Experimentation 61

Experimentation Testing Statistics Metrics 61