Insurance Modeling Predictive Modeling Testing 
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.
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. When business decisions are made based on bad models, the consequences can be severe. As machine learning advances globally, we can only expect the focus on model risk to continue to increase.
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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.
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.
CIO Business Intelligence
JUNE 7, 2022
Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.
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
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.
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