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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 Engineer: A data engineer sets the foundation of building any generating AI app by preparing, cleaning and validating data required to train and deploy AI models.

AI 106
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AIOps vs. MLOps: Harnessing big data for “smarter” ITOPs

IBM Journey to AI blog

Instead, businesses tend to rely on advanced tools and strategies—namely artificial intelligence for IT operations (AIOps) and machine learning operations (MLOps)—to turn vast quantities of data into actionable insights that can improve IT decision-making and ultimately, the bottom line.

Big Data 106
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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. With AWS Glue custom connectors, it’s effortless to transfer data between Amazon S3 and other applications.

AWS 119
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Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions

AWS Machine Learning Blog

Purina used artificial intelligence (AI) and machine learning (ML) to automate animal breed detection at scale. The solution focuses on the fundamental principles of developing an AI/ML application workflow of data preparation, model training, model evaluation, and model monitoring.

AWS 114
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Use Snowflake as a data source to train ML models with Amazon SageMaker

AWS Machine Learning Blog

In order to train a model using data stored outside of the three supported storage services, the data first needs to be ingested into one of these services (typically Amazon S3). This requires building a data pipeline (using tools such as Amazon SageMaker Data Wrangler ) to move data into Amazon S3.

ML 125
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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. DataRobot Data Prep. Sallam | Shubhangi Vashisth. .

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Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio

Flipboard

JuMa is tightly integrated with a range of BMW Central IT services, including identity and access management, roles and rights management, BMW Cloud Data Hub (BMW’s data lake on AWS) and on-premises databases. Furthermore, the notebooks can be integrated into the corporate Git repositories to collaborate using version control.

ML 153