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12 data science certifications that will pay off

CIO Business Intelligence

The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect. Candidates for the exam are tested on ML, AI solutions, NLP, computer vision, and predictive analytics.

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11 most in-demand gen AI jobs companies are hiring for

CIO Business Intelligence

Here are the top 11 roles companies are currently hiring for, or have plans to hire for, to directly address their emerging gen AI strategies. The role of algorithm engineer requires knowledge of programming languages, testing and debugging, documentation, and of course algorithm design.

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Why you should care about debugging machine learning models

O'Reilly on Data

Model debugging is an emergent discipline focused on finding and fixing problems in ML systems. In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. Figure 1 illustrates an example adversarial search for an example credit default ML model.

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The curse of Dimensionality

Domino Data Lab

MANOVA, for example, can test if the heights and weights in boys and girls is different. This statistical test is correct because the data are (presumably) bivariate normal. Statistics developed in the last century are based on probability models (distributions). The accuracy of any predictive model approaches 100%.

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3 Key Components of the Interdisciplinary Field of Data Science

Domino Data Lab

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.

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The most valuable AI use cases for business

IBM Big Data Hub

Promote cross- and up-selling Recommendation engines use consumer behavior data and AI algorithms to help discover data trends to be used in the development of more effective up-selling and cross-selling strategies, resulting in more useful add-on recommendations for customers during checkout for online retailers.

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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.