O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. All predictive models are wrong at times?—just

Risk 359

Risk Modeling Data Processing Software 359

Smarten

MAY 17, 2019

Predictive analytics can help the business to understand online buying behavior, and when, where and how to serve ads, market products and offer discounts or other incentives. Predictive analytics will help you optimize your marketing budget and improve brand loyalty. Learn More: Online Target Marketing Use Case. Customer Targeting.

Predictive Analytics 51

Predictive Analytics Marketing Analytics Predictive Modeling 51

Domino Data Lab

JULY 28, 2021

There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. All models are not made equal. After cleaning, the data is now ready for processing.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

CIO Business Intelligence

JULY 26, 2023

Joe Wilhemy, vice president of Re/Max’s business technology and data platforms, says Re/Max has built several machine learning models and adopted one via an acquisition called “first mover score,” which is designed to inform an agent about contacts in their database who are most likely to list their homes in the near future.

Data Lake 93

Data Lake Digital Transformation Machine Learning Data Architecture 93

Sisense

MARCH 27, 2019

Unlike traditional models that look at historical data for patterns, real-time analytics focuses on understanding information as it arrives to help make faster, better decisions. Finally, real-time BI helps better understand trends and create more accurate predictive models for organizations. Who Uses Real-Time BI?

Business Intelligence 74

Business Intelligence Data Warehouse Predictive Modeling Visualization 74

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks. This is like a denial-of-service (DOS) attack on your model itself.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

John Wheeler

OCTOBER 20, 2020

banking, insurance and securities) measure risk on a quantitative basis. Other quantitative analysis methods are used to develop more precise predictive models to determine the potential for digital risk events, such as product/service liability, fraud or theft.

Risk Management 52

Risk Management Risk Predictive Modeling Insurance 52

Smarten

MAY 16, 2019

Advanced analytics solutions are perfect for credit unions, banks, insurance businesses, auto and real estate loan processes. When applied to the loan approval process, predictive analytics can improve productivity and optimize resources and it can decrease loan defaults and help the business to capitalize on available funds.

Predictive Analytics 40

Predictive Analytics Analytics Predictive Modeling Insurance 40

Cloudera

SEPTEMBER 7, 2023

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. The reality of LLMs and other “narrow” AI technologies is that none of them is turn-key.

Insurance 79

Insurance Risk Data-driven Finance 79

Smarten

JULY 30, 2018

Assisted Predictive Modeling can support business users, IT staff and other users by providing recommendations in gathering, formatting and presenting data to improve the effectiveness and clarity of resulting data and reporting.

Predictive Analytics 40

Predictive Analytics Analytics Predictive Modeling Forecasting 40

Juice Analytics

MARCH 11, 2021

Predictive models to take descriptive data and attempt to tell the future. The right product manager We’ve helped launch data products in many industries including healthcare, education, insurance, advertising and market research. She enhances data through predictive modeling and other advanced data analytics techniques.

Predictive Modeling 128

Predictive Modeling Visualization Reporting Interactive 128

Birst BI

OCTOBER 30, 2018

The output of these algorithms, when used in financial services, can be anything from a customer behavior score to a prediction of future trading trends, to flagging a fraudulent insurance claim. The credit scores generated by the predictive model are then used to approve or deny credit cards or loans to customers.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Smarten

JUNE 26, 2018

Finance – An organization might use this technique to Identify if demographic factors influence banking channel/product/service preference or selection of a type of term plan of an insurance etc. How Can the Chi Square Test of Association Be Used for Business Analysis?

Testing 40

Testing Statistics IT Business Intelligence 40

AWS Big Data

MARCH 7, 2023

It helps you build, train, and deploy models consuming the data from repositories in the data hub. These are just some of the KPIs and metrics that are key for predictive modeling of events as the game acquires new players while keeping existing users involved, engaged, and playing.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

FineReport

APRIL 9, 2024

The integration of clinical data analysis tools empowers healthcare providers to leverage predictive analytics for proactive decision-making. Through the utilization of predictive models, clinicians can forecast patient outcomes and resource needs, enabling early intervention and personalized care delivery.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

O'Reilly on Data

SEPTEMBER 19, 2023

Stage 2: Machine learning models Hadoop could kind of do ML, thanks to third-party tools. While data scientists were no longer handling Hadoop-sized workloads, they were trying to build predictive models on a different kind of “large” dataset: so-called “unstructured data.” And it was good.

Machine Learning 247

Machine Learning Testing Modeling Cost-Benefit 247

Rocket-Powered Data Science

FEBRUARY 12, 2021

The AAI report covers these industries: energy/utilities, financial/insurance, government, healthcare, industrial/manufacturing, life sciences, retail/consumer, services/consulting, technology, telecom, and transportation/airlines. AAI’s recently published “Now and Next State of RPA” report presents detailed results of that survey.

ROI 233

ROI Digital Transformation Reporting Machine Learning 233

DataRobot Blog

MAY 25, 2022

DataRobot enables the user to easily combine multiple datasets into a single training dataset for AI modeling. DataRobot combines these datasets and data types into one training dataset used to build models for predicting whether a building will be damaged in the hurricane. Quickly and Easily Build Models. The Datasets.

Risk 52

Risk Predictive Modeling Insurance Predictive Analytics 52

DataRobot

NOVEMBER 15, 2021

This will be further expanded to energy, life sciences, insurance, government, telecommunications and media organizations in 2022. DataRobot AI Cloud on AWS enables organizations across the banking and healthcare industry to easily build, deploy, and monitor machine learning models that yield actionable insights and ROI.

Manufacturing 52

Manufacturing Forecasting Machine Learning Data-driven 52

CIO Business Intelligence

AUGUST 15, 2023

Shamim Mohammad, CIO, CarMax CarMax That volume created a Sisyphean task for the company’s content writers, as they struggled to provide up-to-date information by make, model, and year for each vehicle in the company’s constantly changing inventory.

IT 91

IT Manufacturing IoT Cost-Benefit 91

Smarten

JULY 10, 2018

Use Case(s): Determine if a product sells better in certain locations, verify if gender has an influence on purchasing decisions, Identify if demographic factors influence banking channel/product/service preference or selection of a type of term insurance plan and more.

Analytics 40

Analytics Forecasting Statistics Sales 40

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade. See Ribeiro et al.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Domino Data Lab

AUGUST 20, 2019

Feature engineering is useful for data scientists when assessing tradeoff decisions regarding the impact of their ML models. It is a framework for approaching ML as well as providing techniques for extracting features from raw data that can be used within the models. We can also modify the features before we start the modeling process.

Testing 68

Testing Modeling Interactive Measurement 68

Smart Data Collective

DECEMBER 12, 2020

An evolving nature of machine learning and unique algorithms are being leveraged within the financial trading industry to compute a large number of data sets to make better and more accurate predictions and to help humans make better and more prudent decisions. Financial Models. Here are the two of the main ways it’s doing so.

Big Data 137

Big Data Machine Learning Finance Predictive Modeling 137

Smarten

JUNE 21, 2018

This article provides a brief explanation of the Holt-Winters Forecasting model and its application in the business environment. Time series forecasting methods are used to extract and analyze data and statistics and characterize results to more accurately predict the future based on historical data.

Forecasting 40

Forecasting Enterprise IT Predictive Modeling 40