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

CIO Business Intelligence

Data scientist As companies embrace gen AI, they need data scientists to help drive better insights from customer and business data using analytics and AI. For most companies, AI systems rely on large datasets, which require the expertise of data scientists to navigate.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? Machine learning and deep learning are both subsets of AI.

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The unreasonable importance of data preparation

O'Reilly on Data

NPR put it well : “the gold standard of scientific studies is to make a single hypothesis, gather data to test it, and analyze the results to see if it holds up. By Wansink’s own admission in the blog post, that’s not what happened in his lab.” 3] Related is the supreme focus on “big 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.

Modeling 219
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R vs Python: What’s the Best Language for Natural Language Processing?

Sisense

In Talking Data , we delve into the rapidly evolving worlds of Natural Language Processing and Generation. Text data is proliferating at a staggering rate, and only advanced coding languages like Python and R will be able to pull insights out of these datasets at scale. A dedicated data expert never stops developing their skills.

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3 Key Components of the Interdisciplinary Field of Data Science

Domino Data Lab

Data science is a field that uses math and statistics as part of a scientific process to develop an algorithm that can extract insights from data. All models are not made equal. After cleaning, the data is now ready for processing. At this stage, data scientists begin writing code for computation and model-building.

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AI in commerce: Essential use cases for B2B and B2C

IBM Big Data Hub

Poorly run implementations of traditional or generative AI technology in commerce—such as deploying deep learning models trained on inadequate or inappropriate data—lead to bad experiences that alienate both consumers and businesses.  The applications of AI in commerce are vast and varied.

B2B 68