Remove Citizen Data Scientist Remove Data Preparation Remove Machine Learning
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Govern generative AI in the enterprise with Amazon SageMaker Canvas

AWS Machine Learning Blog

Launched in 2021, Amazon SageMaker Canvas is a visual point-and-click service that allows business analysts and citizen data scientists to use ready-to-use machine learning (ML) models and build custom ML models to generate accurate predictions without writing any code.

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Predicting the Future of Data Science

Pickl AI

Summary: The future of Data Science is shaped by emerging trends such as advanced AI and Machine Learning, augmented analytics, and automated processes. As industries increasingly rely on data-driven insights, ethical considerations regarding data privacy and bias mitigation will become paramount.

professionals

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3 Takeaways from Gartner’s 2018 Data and Analytics Summit

DataRobot Blog

Today’s data management and analytics products have infused artificial intelligence (AI) and machine learning (ML) algorithms into their core capabilities. These modern tools will auto-profile the data, detect joins and overlaps, and offer recommendations. 2) Line of business is taking a more active role in data projects.

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Data science

Dataconomy

Overview of core disciplines Data science encompasses several key disciplines including data engineering, data preparation, and predictive analytics. Data engineering lays the groundwork by managing data infrastructure, while data preparation focuses on cleaning and processing data for analysis.

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Data scientist

Dataconomy

Data scientists play a crucial role in today’s data-driven world, where extracting meaningful insights from vast amounts of information is key to organizational success. Their work blends statistical analysis, machine learning, and domain expertise to guide strategic decisions across various industries.