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I'm currently looking into big data because it's very interesting to me.
Claire Corthell published a Data Science curriculum that is like an encyclopedia. http://datasciencemasters.org/
The US government publishes a site called http://www.data.gov/ with over 160,000 datasets. "The home of the U.S. Government’s open data Here you will find data, tools, and resources to conduct research, develop web and mobile applications, design data visualizations, and more." As I browsed around, I found a link to the TIGER database of the census. It's a database I was familiar with when I first got out of college.
The image you see at the beginning of this article is from Citymapper, an app that uses public data you can get from Data.gov. I'm about to download it. From the comments, it's a lifechanger for some people.
Are you working with big data? Tell me about it!
O'Reilly Media is offering unlimited 30-day access to the Safari library of over 30,000 books and videos from over 200 publishers and imprints. Keith Spurr called Safari the “best technical learning resource on the internet.” You’ll have instant access to hundreds of books and videos on all aspects of big data--check out this recommended data reading list. Keep up to date on Safari-related news @safari or @safaribot.
Link: http://www.oreilly.com/pub/cpc/1551
O’Reilly Releases their 2015 Data Science Salary Survey
For the third consecutive year, O’Reilly Media conducted an anonymous survey to expose the tools that successful data scientists and engineers use, and how those tool choices might relate to their salary.
Want to know what you need to know to earn the big bucks? Knowledge of certain tools can increase your salary more than getting a Ph.D. Curious what clusters of tools are most commonly used together? Or what job titles pay the best? It's all there.
Gain insight from these potentially career-changing findings, and plug your own variables into one of the linear models to predict your own salary.
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Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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Google has announced the general availability of its C4A virtual machines, marking the debut of Axion-based instances. The cloud provider claims these instances deliver up to 10% better price-performance compared to the latest Arm-based alternatives from competitors, including Amazon Graviton4.
By Renato LosioNetflix extended its prioritized load-shedding implementation to the individual service level to further improve system resilience. The approach uses cloud capacity more efficiently by shedding low-priority requests only when necessary instead of maintaining separate clusters for failure isolation.
By Rafal GancarzWenjie Zi of Grammarly addressed the high failure rates in machine learning at QCon SF 2024, revealing challenges from misaligned business goals to poor data quality. She advocated for a "fail fast" approach and robust MLOps infrastructure, emphasizing that learning from failures can drive success. Clear objectives and rigorous practices are essential for effective implementation.
By Andrew HoblitzellAt QConSF 2024, Cody Yu presented how Anyscale’s Ray can more effectively handle scaling out batch inference. Some of the problems Ray can assist with include scaling large datasets (hundreds of GBs or more), ensuring reliability with spot and on-demand instances, managing multi-stage heterogeneous compute, and managing tradeoffs with cost and latency.
By Andrew HoblitzellAt QCon SF 2024, Faye Zhang gave a talk titled Search: from Linear to Multiverse, covering three trends and techniques in AI-powered search: multi-modal interaction, personalization, and simulation with AI agents.
By Anthony Alford© 2024 Created by Michael Levin. Powered by
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