Remove Artificial Intelligence Remove Data Engineering Remove Data Preparation
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30 Best Data Science Books to Read in 2023

Analytics Vidhya

Introduction Data science has taken over all economic sectors in recent times. To achieve maximum efficiency, every company strives to use various data at every stage of its operations.

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Perform generative AI-powered data prep and no-code ML over any size of data using Amazon SageMaker Canvas

AWS Machine Learning Blog

With over 50 connectors, an intuitive Chat for data prep interface, and petabyte support, SageMaker Canvas provides a scalable, low-code/no-code (LCNC) ML solution for handling real-world, enterprise use cases. Organizations often struggle to extract meaningful insights and value from their ever-growing volume of data.

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Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

AWS Machine Learning Blog

With the integration of SageMaker and Amazon DataZone, it enables collaboration between ML builders and data engineers for building ML use cases. ML builders can request access to data published by data engineers. Additionally, this solution uses Amazon DataZone.

ML 117
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Step-by-step guide: Generative AI for your business

IBM Journey to AI blog

Generative artificial intelligence (gen AI) is transforming the business world by creating new opportunities for innovation, productivity and efficiency. Data Scientists will typically help with training, validating, and maintaining foundation models that are optimized for data tasks.

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State of Machine Learning Survey Results Part Two

ODSC - Open Data Science

First, there’s a need for preparing the data, aka data engineering basics. Machine learning practitioners are often working with data at the beginning and during the full stack of things, so they see a lot of workflow/pipeline development, data wrangling, and data preparation.

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How are AI Projects Different

Towards AI

Michael Dziedzic on Unsplash I am often asked by prospective clients to explain the artificial intelligence (AI) software process, and I have recently been asked by managers with extensive software development and data science experience who wanted to implement MLOps. Norvig, Artificial Intelligence: A Modern Approach, 4th ed.

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Improving air quality with generative AI

AWS Machine Learning Blog

More than 170 tech teams used the latest cloud, machine learning and artificial intelligence technologies to build 33 solutions. This happens only when a new data format is detected to avoid overburdening scarce Afri-SET resources. Having a human-in-the-loop to validate each data transformation step is optional.

AWS 135