Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction.

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Data Science Machine Learning Data Governance Statistics 71

Sanjeev Mohan

FEBRUARY 6, 2019

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline? This is the focus of my latest research which published in Jan 2019. My journey in helping our customers with their technical queries started when I joined Gartner in late 2016. So, why did I decide to write on this topic? I am glad you asked.

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Insight

AUGUST 8, 2019

Whether they’re looking to transition to Data Science, Health Data Science, Data Engineering, Artificial Intelligence, DevOps Engineering, Decentralized Consensus, or Security, Insight Fellows typically already have 90% of the skills they need to succeed in the field. Insight’s model is very different from this.

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Data Science Cost-Benefit Big Data Management 66

IBM Big Data Hub

SEPTEMBER 11, 2023

On June 7, 1983, a product was born that would revolutionize how organizations would store, manage, process , and query their data: IBM Db2. Codd published his famous paper “ A Relational Model of Data for Large Shared Data Banks.” In 1969, retired IBM Fellow Edgar F. Chamberlin and Raymond F.

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Machine Learning Cost-Benefit IoT Data Warehouse 86

Jen Stirrup

JUNE 20, 2020

In efficient data science, we need to take our biases off the table in order to get a true picture of the data we are looking at. Here is the Current Ratio for the past four years for PASS: Year 2019 2018 2017 2016 Quick Ratio ((Current Assets) / Current Liabilities ) 1.03 Let’s see that data for the past few years.

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Domino Data Lab

JANUARY 6, 2019

In Paco Nathan ‘s latest column, he explores the theme of “learning data science” by diving into education programs, learning materials, educational approaches, as well as perceptions about education. He is also the Co-Chair of the upcoming Data Science Leaders Summit, Rev. Learning Data Science.

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Insight

MARCH 18, 2019

As data scientists, machine learning engineers, and AI practitioners, we should be aware of the behaviors of the models we build and check them for biases toward certain attributes, such as race or sex. Want to advance your career in Data Science and Artificial Intelligence? Feel free to get in touch.

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Andrew White

JANUARY 9, 2022

I try to relate as much published research as I can in the time available to draft a response. – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend. – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend.

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O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. 1 again in proposals this year.

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The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. Introduction Time series data appear in a surprising number of applications, ranging from business, to the physical and social sciences, to health, medicine, and engineering.

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Insight

JUNE 10, 2019

In 2016, Uber published its Uber Elevate White Paper , setting its aspirations on providing on-demand air taxis from San Francisco to San Jose for about $130. Alexander | June 1, 2016 Training a c onvolution neural network (CNN) to spot helipads The solution I developed rests on retraining a CNN to recognize helipads in aerial images.

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Rita Sallam

JULY 22, 2016

Gartner revamped the BI and Analytics Magic Quadrant in 2016 to reflect the mainstreaming of this market disruption. Most of the standalone self-service data preparation tools like Paxata, Trifacta, DataWatch, and Lavastorm partner with Tableau, Qlik and Microsoft Power BI. Research VP, Business Analytics and Data Science.

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