CIO Business Intelligence

JULY 18, 2023

Along the way, other uses for the parallel-processing capabilities of Nvidia’s graphical processing units (GPUs) emerged, solving problems with a similar matrix arithmetic structure to 3D-graphics modelling. Some of those models are truly gargantuan: OpenAI’s GPT-4 is said to have over 1 trillion parameters.

Manufacturing 91

Manufacturing Forecasting Software Marketing 91

CIO Business Intelligence

SEPTEMBER 6, 2022

It launched its first online-only brand, Very, in 2009 and finally abandoned its printed catalogs to go all-in online in 2015. It was very fragmented, and I brought it together into a hub-and-spoke model.”. The new model enables Very to design once and deploy everywhere, while maintaining a product focus. Where do we store it?

IT 74

IT Forecasting Data Lake Enterprise 74

DataRobot

APRIL 12, 2021

In 2009, an Iridium Communications satellite and a Soviet-era satellite collided 500 miles above Siberia, creating thousands of pieces of debris. Improving the modeling of space. Achieving that goal will require sophisticated AI modeling and machine learning. To date there has been only one serious in-space collision.

Software 52

Software Machine Learning Dashboards Modeling 52

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

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

BizAcuity

APRIL 25, 2022

From 2009 to 2019, in a span of 10 years, the United States tripled its gross gaming revenue from $34.3 A predictive model that’s gaining traction in the casino business is Recency-Frequency-Monetary (RFM) model. In studying customer behavior, an AI model is trained to identify the right offer for the right player.

Marketing 52

Marketing Strategy ROI Digital Transformation 52

bridgei2i

MAY 26, 2020

It is even more essential now that supply chains are empowered with a high standard of data and analytics sophistication to be able to cost-effectively serve the company’s purpose and combat risks at the same time. You know, Chief Risk Officers, for example, will no longer be confined to the credit industry. Anushruti: Perfect.

Enterprise 131

Enterprise Management Forecasting Manufacturing 131

Domino Data Lab

MAY 20, 2021

In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed. This carries the risk of this modification performing worse than simpler approaches like majority under-sampling. Chawla et al. Indeed, in the original paper Chawla et al. UCI machine learning repository.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Domino Data Lab

APRIL 21, 2021

We’ll use a gradient boosting technique via XGBoost to create a model and I’ll walk you through steps you can take to avoid overfitting and build a model that is fit for purpose and ready for production. This is generally problematic, as the model trained on such data will have difficulties recognising the minority class.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Peter James Thomas

AUGUST 12, 2018

A clear parallel would be credit risk in Retail Banking, but something as simple as an estimate of potentially delinquent debtors is an inherently statistical figure (albeit one that may not depend on the output of a statistical model). A model may for example spit out a figure like £12.4 The model is not saying that £12.4

Metrics 49

Metrics Statistics Data Quality Measurement 49

Jet Global

JUNE 15, 2021

In 2006, FAS123R contained new standards, which were reclassified in 2009 as ASC718. A number of different pricing models exist to determine the worth of such shares. ASC 718 guidelines do not dictate that you use any one model. Standardization began in the mid-2000s with FAS123R. ASC 718 Reporting Best Practices.

Reporting 52

Reporting Recreation/Entertainment Finance Cost-Benefit 52

Cloudera

SEPTEMBER 4, 2018

And like background fireworks, the global banks have lit up their share of headlines, posting record fines (exceeding 342 billion dollars between the US and EU since 2009) for misconduct, including violation of anti-money laundering rules. History tells us that the AML landscape is constantly changing.

Reporting 43

Reporting Finance Sales Marketing 43

Domino Data Lab

JULY 9, 2019

When he retired in 2009 he had some time on his hands. One of the ways I frame that is, “Are you looking to build a predictive model? or a prescriptive model? or a descriptive model?” What you really want is a prescriptive model. The “what” is a topic model.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Occam's Razor

SEPTEMBER 29, 2009

Ideally you'll measure the number prior to your branding campaign, say Feb 2009, and then you'll measure it again during your campaign, March 2009. When you are trying to break through the noise you'll take any measure of success to detect a signal, use the macro & micro conversion mental model.

Measurement 128

Measurement Metrics Analytics Marketing 128