Discover and read the best of Twitter Threads about #datascientists

Most recents (5)

Why mid-sized companies are behind the #datascience curve: A thread—
Mid-sized companies are behind in terms of being data-driven when compared to startups and large entities. There are several reasons for this which puts them at a disadvantage.
1/ The average age of a mid-sized company is c years. X years older than the average startup and large entities such as Facebook or Apple. Overall, their workforce is older as well which translates into greater domain knowledge and also little technical capability.
2/ There is often a greater majority of non-technical works which places a heavy burden on the few technical workers often leading to burnout, limitations and ultimately churn.
Read 11 tweets
#Event201 begins. Check it out online to participate virtually! centerforhealthsecurity.org/event201/ #pandemic #biosecurity
Global leaders in business and government have convened to address the pandemic situation. @T_Inglesby from @JHSPH_CHS Moderates. See the #Event201 website for details on the participants.
Global distribution of cases and deaths from #Event201
Read 45 tweets
Love the simplicity of #Serverless #FaaS (Function-as-a-Service) but hate the setup process? Look to these 7 open source projects to ease #AWS Lambda deployments: dy.si/M3VJd
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#BigData #StreamingAnalytics #Cloud #DataScience #MachineLearning #IFTTT #EventDriven #AI
13 free tools for #API design, development, & testing — for example, Amazon API Gateway allows you to build front-end APIs for applications built on Amazon EC2, #AWS Lambda, or any web application:
dy.si/1VTf942
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#microservices #cloud #serverless #FaaS #coding #IoT
#IFTTT alternatives for developers of #EventDriven workflows: dy.si/ZorG2N
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#IoT #EdgeAnalytics #EdgeComputing #Microservices #DataScience #BigData #FaaS #ML
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+See the book “AWS Lambda in Action: Event-driven #Serverless Applications” at amzn.to/2YFDSO8
Read 4 tweets
#Bigdata vs Machine Learning vs Artificial Intelligence
By Irene Aldridge
☝️author High-Frequency Trading: A Practical Guide to #Algorithmic Strategies& #Trading Systems
☝️co-author Real-Time Risk: What Investors Should Know About #Fintech,#highfrequencytrading and FlashCrashes
1. ☝️🧐➿🔢 In traditional #statistics or #econometrics, researchers make assumptions about #data distributions ahead of the analysis
2. 🥇💪#machinelearning = the 1st discipline to apply #efficiency to #problemsolving brought by #computers & their enhanced computational power
3. 🤗➿🔢#ML scientists try to reduce #assumptions about the data as much as possible&let the data (&computers) decide what fits best.
4. ♾➡️🔤🌐#Datascience identifies core characteristics of the data, summarized by what has been known as #characteristic values (#eigenvalues)
Read 6 tweets
1/6 Data and the Quest for Truth: A short cartoon talking about the value of data in establishing truth. First, distinguish between matters of opinion and matters of fact.

#datascience #scientificmethod #machinelearning

#think2018 #IBMPartner @ibmanalytics
2/6 You can have a preference and that’s cool. You like one thing. I like another. We run into problems when we argue about verifiable facts. Watch out for #confirmationbias

#datascience #analytics #confirmationbias

#think2018 #IBMPartner
3/6 Ignoring evidence can impact people around you… and that’s bad. We live in a #BigData in which everything is quantified. To solve our problems, we need to become data-literate.

#datascience #machinelearning

#think2018 #IBMPartner
Read 6 tweets

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