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5 Actionable Insights to Make You Stand Out in Data Science

Dataconomy

In 2009, Hal Varian (Google’s Chief Economist) famously joked that “the sexiest job in the next 10 years will be Statistics”. 118,709 – the average salary for a Data Scientist today (according to Glassdoor). The post 5 Actionable Insights to Make You Stand Out in Data Science appeared first on Dataconomy.

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Mastering digital transformation strategy: A comprehensive guide for success

Data Science Dojo

In 2009, Uber came along and revolutionized the entire taxi business. The term “digital transformation” is broad enough to encompass everything from “IT modernization” (such as cloud computing) to “digital optimization” (such as “big data”) to “new digital business models.”

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Fast and cost-effective LLaMA 2 fine-tuning with AWS Trainium

AWS Machine Learning Blog

His research interest is in systems, high-performance computing, and big data analytics. Huan works on AI and Data Science. He was a recipient of the NSF Faculty Early Career Development Award in 2009. From 2015–2018, he worked as a program director at the US NSF in charge of its big data program.

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Will private data work in a new-era AI world?

Dataconomy

One of the key questions we started from was: are most companies running the same frontier AI models, is incorporating their data the only way they have a chance to differentiate? Is data really a moat for enterprises? At that time, they weren’t even digital enterprises; the digital transformation hadn’t occurred yet.

AI 113
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Frugality meets Accuracy: Cost-efficient training of GPT NeoX and Pythia models with AWS Trainium

AWS Machine Learning Blog

The project was awarded 2009 National medal of Technology and Innovation. Dr. Huan works on AI and Data Science. He was a recipient of the NSF Faculty Early Career Development Award in 2009. Before joining AWS, he worked at Baidu research as a distinguished scientist and the head of Baidu Big Data Laboratory.

AWS 127
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Amazon SageMaker built-in LightGBM now offers distributed training using Dask

AWS Machine Learning Blog

Distributed training is a technique that allows for the parallel processing of large amounts of data across multiple machines or devices. By splitting the data and training multiple models in parallel, distributed training can significantly reduce training time and improve the performance of models on big data.

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When data and health converge: How the healthcare industry is turning to data science to curb future pandemics

Dataconomy

Data science – that is the gathering, analysis and use of data – plays a central role in our modern world. From Big Tech to transportation, commerce through to government, it has been revolutionary in many aspects of our life, and healthcare is no exception. What is the role of data science in healthcare?