PLURALSIGHT.BUILDING.DEEP.LEARNING.MODELS.USING.APACHE.MXNET-JGTiSO

Section
Appz
Group
JGTiSO
Size
240,30 MB
Files
19
Date
2018-09-23

NFO

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        ███  ▀  * Title..: Pluralsight Building Deep Learning Models Using Apache MXNet           
        ███     * Date...: 23-09-2018
   ▄    ███     * Type...: Bookware  
    ▀▓███▓▓ █   * Disks..: 17x15mb   
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   ░▒▓██████▀ ▄▀  ▀▓▀     Release notes:
        ▄▄▄
        ███   Apache MXNet offers low-level and high-level APIs which is
        ███   key to efficiently build neural networks. It also allows you
        ███   to construct static and dynamic graphs in a symbolic manner
        ███   using the Module API, the Symbol API, or the Gluon API. In
        ███   this course, Building Deep Learning Models Using Apache
        ███   MXNet, you'll learn the basic building blocks of building
        ███   neural networks using NDArrays, the Module API, the Symbol
        ███   API, as well as the cutting edge Gluon API. First, you'll
        ███   gain an understanding of the basic architecture of MXNet and
        ███   how the basic data structure NDArrays work. Next, you'll
        ███   discover the difference between symbolic and imperative
        ███   programming and when you would choose to use one over the
        ███   other. Then, you'll discover the use of optimizers, loss
        ███   functions, and data iterators in building and executing
        ███   neural networks. Finally, you'll explore the Gluon API and
        ███   build a convolutional neural network for image
        ███   classification and hybridize it in order to execute a static
        ███   computation graph. By the end of this course, you'll have
        ███   the confidence to efficiently build and execute neural
        ███   networks using all of the APIs that Apache MXNet has to
        ███   offer.
        ███   
        ███   
        ███   More info: 
        ███   https://www.pluralsight.com     
        ███   
        ███   Install notes:
        ███	
        ███   Unrar, Learn and Enjoy!
        ███
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       ▀▀▀▀  █ ▓▓  ▄  ▀         GREETINGS:
   ░▒▓██████▀ ▄▀  ▀▓▀
        ▄▄▄              AOD, CLASS, CROSSFiRE, JiOO, SAC, BBL
        ███              EVILISO, 4KIDS, SHOCK, MAGE, DYNAMiCS
        ███
        ███▄▀ ▄▀         Big thanks to all JGT sites, and
        ███▌ ██ ▒        sites accepting us!
        ▓██▓▄ ▀▄                                    ▄▄▄▄▄▄▄
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               ███  in memory of   ▀ ▄█▀▀  ▄▀   drawn by the honored
               ███    THEPROF       ▀                  FX/SAC
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                             "judgement day is near..."


Files

PathSize
jgt-pbdlmu.r0014,31 MB
jgt-pbdlmu.r0114,31 MB
jgt-pbdlmu.r0214,31 MB
jgt-pbdlmu.r0314,31 MB
jgt-pbdlmu.r0414,31 MB
jgt-pbdlmu.r0514,31 MB
jgt-pbdlmu.r0614,31 MB
jgt-pbdlmu.r0714,31 MB
jgt-pbdlmu.r0814,31 MB
jgt-pbdlmu.r0914,31 MB
jgt-pbdlmu.r1014,31 MB
jgt-pbdlmu.r1114,31 MB
jgt-pbdlmu.r1214,31 MB
jgt-pbdlmu.r1314,31 MB
jgt-pbdlmu.r1414,31 MB
jgt-pbdlmu.r1511,41 MB
jgt-pbdlmu.rar14,31 MB
jgt-pbdlmu.sfv425 B
jgtiso.nfo6,32 KB