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The quest for high-quality data

O'Reilly on Data

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. Data integration and cleaning.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes. Data analytics vs. business analytics. Business analytics is another subset of data analytics.

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Why you should care about debugging machine learning models

O'Reilly on Data

More structured approaches to sensitivity analysis include: Adversarial example searches : this entails systematically searching for rows of data that evoke strange or striking responses from an ML model. Figure 1 illustrates an example adversarial search for an example credit default ML model.

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AI In Analytics: Today and Tomorrow!

Smarten

Assisted Predictive Modeling and Auto Insights to create predictive models using self-guiding UI wizard and auto-recommendations The Future of AI in Analytics The C=suite executive survey revealed that 93% felt that data strategy is critical to getting value from generative AI, but a full 57% had made no changes to their data.

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Proposals for model vulnerability and security

O'Reilly on Data

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. It seems entirely possible to do the same with customer or transactional data.

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