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          • DLtrain Model
        • Data-Set
          • IBM Cloud Object Storage
          • MNIST++
        • Train DL Model
          • CoLab
          • TF On Prime CPU
          • Build DLtrain in Power 9
          • Build DLtrain for jetson Nano
          • Build DLtrain in Docker x86
          • DLtrain in Windows M/C
          • DLtrain On Prime CPU
        • Save and Load
        • Inference
          • Flask Micro Service
          • Inference via JavaScript
          • Deploy in Cloud
          • Android Phone
          • Jetson Nano TF Model
          • Jetson Nano DLtrain
          • Near Edge
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      • Sambhram
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      • CV Raman Global Univ
        • Thanks
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        • AI in Monitoring MG
        • IoT sensors
        • Interpret Measurements
        • Edge in Microgrid
        • DLtrain in Jetson Nano
        • AI in Smart phone
        • Deploy AI in Sensors
        • Thank You
      • Dayananda Sagar
      • Nirma University -CPS Y22
        • Thanks to Nirma Univ
        • DL in Microgrid
        • Kanshi
        • AI in Security
        • Pontryagin Observer
        • Pontryagin Duality
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        • CPS
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        • Modern Physics
        • Optics
        • Electricity and Magnetism
        • Thermal Physics
        • Mechanics
        • General
      • Maths
        • Integral calculus
        • Differential calculus
        • Vectors
        • Trigonometry
        • Probability
        • Matrices and Determinants
        • Binomial Theorem
        • Permutation and Combination
        • Logarithms
        • Sequence and Series
        • Quadratic Equations
        • Complex Numbers
      • Chemistry
        • Physical Chemistry
        • Organic Chemistry
        • Inorganic Chemistry
  • DL in IoT Edge
    • Edge Infra
      • Compute via CUDA
        • Introduction
        • Vector Add in CUDA
        • MAT Mul in CUDA
          • tst1.py
          • tst2.py
          • tst3.py
          • tst4.py
        • Reference
    • Jetson Nano
      • Setting Up
        • Resources
        • Installation
        • First Boot
        • JetPack
        • IO
        • Internet Access via Wi-Fi
        • RDP / SSH
        • git
        • nvcc
        • cmake 3.14
        • Python
      • Quick Demo
      • Hello World
      • Kernel Update
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      • Android SDK
      • Android NDK
      • J7 Source Code
      • Credential Update
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      • Generate APK
      • Install APK in Phone
      • Using J7
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      • jkhome
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      • Deep Learning
        • Data Science
          • Maths for Data Science
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          • Statistics for Data Science
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        • Boltzmann Machine
          • Digital Twin Phy
          • Prof G E Hinton
          • Quantum Mechanics
      • jkEvents
        • PRIST University
        • IETEevent
        • Baranovichi
          • Model
            • TF Model
            • DLtrain Model
          • Data-Set
            • IBM Cloud Object Storage
            • MNIST++
          • Train DL Model
            • CoLab
            • TF On Prime CPU
            • Build DLtrain in Power 9
            • Build DLtrain for jetson Nano
            • Build DLtrain in Docker x86
            • DLtrain in Windows M/C
            • DLtrain On Prime CPU
          • Save and Load
          • Inference
            • Flask Micro Service
            • Inference via JavaScript
            • Deploy in Cloud
            • Android Phone
            • Jetson Nano TF Model
            • Jetson Nano DLtrain
            • Near Edge
            • DL Model Update
        • Sambhram
          • Digital Twin
          • Edge Ready
          • BO
          • Startups
          • MBA induction Y22
        • CV Raman Global Univ
          • Thanks
          • Microgrid
          • AI in Monitoring MG
          • IoT sensors
          • Interpret Measurements
          • Edge in Microgrid
          • DLtrain in Jetson Nano
          • AI in Smart phone
          • Deploy AI in Sensors
          • Thank You
        • Dayananda Sagar
        • Nirma University -CPS Y22
          • Thanks to Nirma Univ
          • DL in Microgrid
          • Kanshi
          • AI in Security
          • Pontryagin Observer
          • Pontryagin Duality
          • Daily Inspection
          • Boltzmann2NN
          • CPS
          • Russell
          • IIOT4pointZero
          • QandA
          • Abstract
          • Test
        • PMU
      • STEM
        • Physics
          • Modern Physics
          • Optics
          • Electricity and Magnetism
          • Thermal Physics
          • Mechanics
          • General
        • Maths
          • Integral calculus
          • Differential calculus
          • Vectors
          • Trigonometry
          • Probability
          • Matrices and Determinants
          • Binomial Theorem
          • Permutation and Combination
          • Logarithms
          • Sequence and Series
          • Quadratic Equations
          • Complex Numbers
        • Chemistry
          • Physical Chemistry
          • Organic Chemistry
          • Inorganic Chemistry
    • DL in IoT Edge
      • Edge Infra
        • Compute via CUDA
          • Introduction
          • Vector Add in CUDA
          • MAT Mul in CUDA
            • tst1.py
            • tst2.py
            • tst3.py
            • tst4.py
          • Reference
      • Jetson Nano
        • Setting Up
          • Resources
          • Installation
          • First Boot
          • JetPack
          • IO
          • Internet Access via Wi-Fi
          • RDP / SSH
          • git
          • nvcc
          • cmake 3.14
          • Python
        • Quick Demo
        • Hello World
        • Kernel Update
      • J7 App
        • Android SDK
        • Android NDK
        • J7 Source Code
        • Credential Update
        • J7Build
        • Generate APK
        • Install APK in Phone
        • Using J7
      • IBM Watson VR
        • Watson AI
        • Watson Studio
        • Watson VR service
        • Custom Model
        • Train
        • Test
        • Deploy
        • Client APP
        • Recap
      • IoTin5G
        • Part 1
        • Part 2
        • Part 3
      • Open Power
        • A2O
        • Open-CE
        • TL-V
      • Applications
        • sports
        • Agriculture
        • Gesture Recognition
        • Nalla Paru
        • Ventilator
          • Biocontainment
          • Auscultation
          • Nurse
          • IoT Edge
        • Accelerated Inference
        • Webb Science

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One Teacher able to handle not more than 40 students, But Power AC922 expected to handle 2000 plus CUDA cores and 100 plus Tensor Cores, when AI workload assigned to Power AC922.
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