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Basil Faruqui, BMC: Why DataOps needs orchestration to make it work

AI News

Analysts and thought leaders almost universally urge the importance of the CEO being actively involved in data initiatives. But what gets buried in the small print is the acknowledgement that many data projects never make it to production. In 2016, Gartner assessed it at only 15%. It’s all data driven,” Faruqui explains.

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Taking Pandas To The Next Level With LLMs

Mlearning.ai

Photo by Andrew Neel on Unsplash Introduction If you are working or have worked on any data science task then you definitely used pandas. So, pandas is a library which helps with performing data ingestion and transformations. apply(lambda x: x.year) df.groupby('year')['Sales'].mean() Yearly average sales.

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TensorFlow vs. PyTorch: What’s Better for a Deep Learning Project?

Towards AI

TensorFlow Extended (TFX): End-to-End Pipeline: Providing a variety of tools and libraries for production-ready machine learning pipelines, TFX takes care of the entire lifecycle from data ingestion and validation to model training, evaluation, and deployment. So, let’s take a look at PyTorch.

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Improving air quality with generative AI

AWS Machine Learning Blog

This manual synchronization process, hindered by disparate data formats, is resource-intensive, limiting the potential for widespread data orchestration. The platform, although functional, deals with CSV and JSON files containing hundreds of thousands of rows from various manufacturers, demanding substantial effort for data ingestion.

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Celebrating 40 years of Db2: Running the world’s mission critical workloads

IBM Journey to AI blog

Many consider a NoSQL database essential for high data ingestion rates. In 2016, Db2 for z/OS moved to a continuous delivery model that provides new capabilities and enhancements through the service stream in just weeks (and sometimes days) instead of multi-year release cycles.

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HAYAT HOLDING uses Amazon SageMaker to increase product quality and optimize manufacturing output, saving $300,000 annually

AWS Machine Learning Blog

Data ingestion HAYAT HOLDING has a state-of-the art infrastructure for acquiring, recording, analyzing, and processing measurement data. Two types of data sources exist for this use case. Since 2016 he mentored hundreds of entrepreneurs at startup incubation programs pro-bono.

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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

In 2010, WorldQuant was producing several thousand alphas per year, by 2016 had one million alphas, by 2022, had multiple millions, with a stated ambition to get to 100 million alphas. The automated process of data ingestion, processing, packaging, combination, and prediction is referred to by WorldQuant as their “alpha factory.”

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