|||

There is a seemingly myriad of terms to describe people who interact with models

There is a seemingly myriad of terms to describe people who interact with models. Just a few terms that are currently in usage include researchers, data scientists, machine learning researchers, machine learning engineers, data engineers, infrastructure engineers, DataOps, DevOps, etc. Both Miner and Presser commented upon and agreed that before any assignment of any term, the work itself existed previously. Presser defines data engineering as embodying the skills to obtain data, build data stores, manage data flows including ETL, and provide the data to data scientists for analysis. Presser also indicated that data engineers at large enterprise organizations also have to be well versed in “cajoling” data from departments that may not, at first glance, provide it. Miner agreed and indicated that there is more thought leadership around the definition of data science versus data engineering which contributes to the ambiguity within the market. — https://blog.dominodatalab.com/collaboration-data-science-data-engineering-true-false/
    Next → → I’ve never heard of anybody having a data engineering undergrad class, but you’re starting to hear data science classes pop up https://blog.dominodatalab.com/collaboration-data-science-data-engineering-true-false/ ← Previous → Over the past five years, we have heard many stories from data science teams about their successes and challenges when building, deploying, and monitoring models https://blog.dominodatalab.com/collaboration-data-science-data-engineering-true-false/
    Latest posts
    Reuters → Systemic lessons from South Korea’s Patient 31
    Axle → Divide & conquer
    FSG → Can Snow Clearing Be Sexist?
    The Verge → As Lambda students speak out, the school’s debt-swapping partnership disappears from the internet
    The Talk Show → “Bring It On, Haters”, With Special Guest Ben Thompson
    Facebook → Starting the Decade by Giving You More Control Over Your Privacy
    Motherboard → Leaked Documents Expose the Secretive Market for Your Web Browsing Data
    The Verge → Google’s ads just look like search results now
    MacMillan → Interference by Sue Burke
    Systemics and design principles in support of Tiago Forte’s PARA framework
    → Microsoft wants to capture all of the carbon dioxide it’s ever emitted
    → US announces AI software export restrictions for China
    → Science Conferences Are Stuck in the Dark Ages
    → This wireless power startup says it can charge your phone using only radio waves
    → Segway’s newest self-balancing vehicle is an egg-shaped wheelchair
    → Twitter announces Bluesky: a team seeking and developing an open standard for social media
    → Elon Musk attempts to explain Twitter to normal people in court
    → TED and YouTube launch global climate initiative
    → Embracing multilingualism to enhance complexity sensitive research
    → The ‘Amazon effect’ is flooding a struggling recycling system with cardboard
    → John Kerry, Arnold Schwarzenegger wage ‘World War Zero’ on climate change
    → Combining semantic and term frequency similarities for text clustering
    → Bad RCS implementations are creating big vulnerabilities, security researchers claim
    → 2019 Tech Trends Report — The Future Today Institute
    → Medical Crowdsourcing: Harnessing the “Wisdom of the Crowd” to Solve Medical Mysteries
    → Report Launch - OPSI Primer on AI for the Public Sector
    → “Level Up”: Leveraging Skill and Engagement to Maximize Player Gameplay
    → Beautiful is Good and Good is Reputable: Multiple-Attribute Charity Website Evaluation and Initial Perceptions of Reputation Under the Halo Effect
    → Piret Tõnurist & Systems Change: how to get started and keep going?
    → IBM expert Tamreem El Tohamy on bridging the skills gap in Africa
    → The changing work of innovation for public value and social impact