IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language.

Cost-Benefit 97

Cost-Benefit Modeling Manufacturing Interactive 97

FineReport

DECEMBER 11, 2019

. – Head First Data Analysis: A learner’s guide to big numbers, statistics, and good decisions. Effective use of big data helps companies analyze critical information more accurately, ultimately improving operational efficiency, reducing costs, reducing risk, accelerating innovation, and increasing revenue.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

Ontotext

APRIL 3, 2024

Nimit Mehta: I think that 2024 is going to be a buckle-down year, but, at the same time, we’ll see a rapid explosion of experimentation. Nimit Mehta : You are talking about the three big ones: cost, revenue, and risk. And, when you get to the top, it’s about risks and existential threats to the business. What is risk?

Technology 59

Technology Risk Digital Transformation Measurement 59

Domino Data Lab

JANUARY 24, 2019

These solutions help data analysts build models by automating tasks in data science, including training models, selecting algorithms, and creating features. These tools support a breadth of use cases including data science, data engineering, and model operations. Proprietary (often GUI-driven) data science platforms.

Data Science 65

Data Science Marketing Data-driven Statistics 65

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

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 Strategy 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

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? It’s important to understand that ChatGPT is not actually a language model. It’s a convenient user interface built around one specific language model, GPT-3.5, The GPT-series LLMs are also called “foundation models.” GPT-2, 3, 3.5,

IT 262

IT Modeling Testing Risk 262

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

Enterprise 311

Enterprise Deep Learning Data Governance Risk 311

CIO Business Intelligence

DECEMBER 6, 2023

Some of the most vocal complaints about generative AI have come from authors and artists unhappy at having their work used to train large language models (LLMs) without permission. But these Guardian polls appear to have been published on Microsoft properties with millions of visitors by automated systems with no human approval required.

IT 133

IT Risk Management Interactive Modeling 133

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

Occam's Razor

JUNE 4, 2018

I mean developing and inserting a subtle collection of gentle nudges that can help increase the conversion rate by a statistically significant amount. Not easy, but your business model has to change to survive.). Not wanting to risk it, I click on the Find in Store link you see at the bottom of the page. Sizing the Opportunity.

Strategy 124

Strategy Cost-Benefit Testing Sales 124

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Introduction. 2018-06-21).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

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. Yet, this challenge is not insurmountable. for what is and isn’t possible) to address these challenges.

Management 110

Management Machine Learning Experimentation Metrics 110

The Unofficial Google Data Science Blog

MAY 31, 2016

A geo experiment is an experiment where the experimental units are defined by geographic regions. Statistical power is traditionally given in terms of a probability function, but often a more intuitive way of describing power is by stating the expected precision of our estimates. They are non-overlapping geo-targetable regions.

Advertising 42

Advertising Testing Sales Statistics 42

O'Reilly on Data

DECEMBER 9, 2019

Recall from my previous blog post that all financial models are at the mercy of the Trinity of Errors , namely: errors in model specifications, errors in model parameter estimates, and errors resulting from the failure of a model to adapt to structural changes in its environment.

Statistics 27

Statistics Uncertainty Risk Marketing 27

AWS Big Data

JULY 3, 2023

This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance. Our model portfolio will buy stocks that are added to the index, known as going long, and will sell an equivalent amount of stocks removed from the index, known as going short.

Snapshot 85

Snapshot Data Lake Testing Strategy 85

Occam's Razor

NOVEMBER 17, 2008

There is a tendency to think experimentation and testing is optional. 4 Big Bets, Low Risks, Happy Customers. You have just launched something risky, yet you have controlled the risk by reducing exposure of the risky idea. You can control the risk you want to take. # But remember you can control risk.

Testing 112

Testing Experimentation Risk Optimization 112

Cloudera

NOVEMBER 25, 2020

How can he make it easy to see statistics, and do calculations, on discovered commonalities, across structured and unstructured data? And most importantly, once shared security model across data sets and compute accessing the data. It would enable faster experimentation with easy, protected, and governed access to a variety of data.

Data Warehouse 58

Data Warehouse Unstructured Data Analytics Visualization 58

Occam's Razor

JANUARY 9, 2012

I've discovered that if we can just get them to imagine a better existence, undertake serious risks, experiment with new better ideas, and spend money executing them… they will ask for more robust measurement! Our mental model has not shifted enough to the existing reality. AND you can control for risk!

Marketing 140

Marketing B2B Measurement Risk 140

Domino Data Lab

AUGUST 26, 2019

Data scientists, machine learning (ML) researchers, and business stakeholders have a high-stakes investment in the predictive accuracy of models. Data scientists and researchers ascertain predictive accuracy of models using different techniques, methodologies, and settings, including model parameters and hyperparameters.

Testing 79

Testing Modeling Machine Learning Metrics 79

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 118

Analytics Consulting Metrics Experimentation 118

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

IBM Big Data Hub

SEPTEMBER 25, 2023

Uber’s DNA as an analytics company At its core, Uber’s business model is deceptively simple: connect a customer at point A to their destination at point B. Large, untested workloads run the risk of hogging all the resources. In some cases, the queries run out of memory and do not complete. It lands as raw data in HDFS.

OLAP 95

OLAP Data Lake Data-driven Snapshot 95