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Saturday, 21 May 2016 07:26

Learning About Deep Learning

The concept is certainly compelling. Having a machine capable of reacting to real-world visual, auditory or other type of data and then responding, in an intelligent way, has been the stuff of science fiction until very recently. We are now on the verge of this new reality with little general understanding of what it is that artificial intelligence, convolutional neural networks, and deep learning can (and can’t) do, nor what it takes to make them work. At the simplest level, much of the current efforts around deep learning involve very rapid recognition and classification of objects—whether visual, audible, or some other form of digital data. Using cameras, microphones and other types of sensors, data is input into a system that contains a multi-level set of filters that provide increasingly detailed levels of differentiation. Think of it like the animal or plant classification charts from your grammar school days: Kingdom, Phylum, Class, Order, Family, Genus, Species.

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  • A synergetic R-Shiny portal for modeling and tracking of COVID-19 data
    A synergetic R-Shiny portal for modeling and tracking of COVID-19 data

    Dr. Mahdi Salehi, an associate member of SDAT and assistant professor of statistics at the University of Neyshabur, introduced a useful online interactive dashboard that visualize and follows confirmed cases of COVID-19 in real-time. The dashboard was publicly made available on 6 April 2020 to illustrate the counts of confirmed cases, deaths, and recoveries of COVID-19 at the level of country or continent. This dashboard is intended as a user-friendly dashboard for researchers as well as the general public to track the COVID-19 pandemic, and is generated from trusted data sources and built-in open-source R software (Shiny in particular); ensuring a high sense of transparency and reproducibility.

    Access the shiny dashboard: https://mahdisalehi.shinyapps.io/Covid19Dashboard/

    Written on Friday, 08 January 2021 07:03 in SDAT News Read 4532 times Read more...
  • First Event on Play with Real Data
    First Event on Play with Real Data

    Scientific Data Analysis Team (SDAT) intends to organize the first event on the value of data to provide data holders and data analyzers with an opportunity to extract maximum value from their data. This event is organized by International Statistical Institute (ISI) and SDAT hosted at the Bu-Ali Sina University, Hamedan, Iran. 

    Organizers and the data providers will provide more information about the goals of the initial ideas, team arrangement, competition processes, and the benefits of attending this event on a webinar hosted at the ISI Gotowebianr system. Everyone invites to participate in this webinar for free, but it is needed to register at the webinar system by 30 December 2020. 

    Event Time: 31 December 2020 - 13:30-16:30 Central European Time (CET)

    Register for the webinar: https://register.gotowebinar.com/register/8913834636664974352 

    More details about this event: http://sdat.ir/en/playdata 

    Aims and outputs:

    • Playing with real data by explorative and predictive data analysis techniques 
    • A platform between a limited number of data providers and hundreds to thousands of data scientist Teams
    • Improving creativity and scientific reasoning of data scientist and statisticians 
    • Finding the possible “bugs” with the current data analysis methods and new developments
    • Learn different views about a dataset.

    AWARD-WINNING:

    The best-report awards consist of a cash prize:
    $400 for first place,
    $200 for second place, and
    $100 for third place.

    Important Dates: 

    Event Webinar: 31 December 2020 - 13:30-16:30 Central European Time (CET). 
    Team Arrangement: 01 Jan. 2021 - 07 Jan. 2021
    Competition: 10 Jan. 2021 - 15 Jan. 2021
    First Assessment Result: 25 Jan. 2021
    Selected Teams Webinar: 30 Jan. 2021
    Award Ceremony: 31 Jan. 2021

    Please share this event with your colleagues, students, and data analyzers. 

    Written on Wednesday, 23 December 2020 13:45 in SDAT News Read 4800 times Read more...
  • Development of Neuroimaging Symposium and Advanced fMRI Data Analysis
    Development of Neuroimaging Symposium and Advanced fMRI Data Analysis

    The Developement of Structural and Functional Neuroimaging Symposium hold at the School of Sciences, Shiraz University in April 17 2019.  The Advanced fMRI Data Analysis Workshop also held in April 18-19 2019. For more information please visit: http://sdat.ir/dns98 

    Written on Sunday, 21 April 2019 12:18 in SDAT News Read 4932 times Read more...
  • Releasing Rfssa Package by SDAT Members at CRAN
    Releasing Rfssa Package by SDAT Members at CRAN

    The Rfssa package is available at CRAN. Dr. Hossein Haghbin and Dr. Seyed Morteza Najibi (SDAT Members) have published this package to provide the collections of necessary functions to implement Functional Singular Spectrum Analysis (FSSA) for analysing Functional Time Series (FTS). FSSA is a novel non-parametric method to perform decomposition and reconstruction of FTS. For more information please visit github homepage of package. 

    Written on Sunday, 03 March 2019 21:03 in SDAT News Read 3524 times
  • Data Science Symposium
    Data Science Symposium

    Symposium of Data Science Developement and its job opportunities hold at the Faculty of Science, Shiraz University in Feb 20 2019. For more information please visit: http://sdat.ir/dss97 

    Written on Friday, 01 February 2019 00:13 in SDAT News Read 5019 times Read more...

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SDAT is an abbreviation for Scientific Data Analysis Team. It consists of groups who are specialists in various fields of data sciences including Statistical Analytics, Business Analytics, Big Data Analytics and Health Analytics. 

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