TensorFlow MCQ

  1. TensorFlow is a free and open-source ............. based library for machine learning.
  2. TensorFlow is developed by .................
  3. TensorFlow was initially released in .................
  4. Tensorflow is written in which language?
  5. Tensorflow attracts the largest popularity on GitHub compare to the other deep learning framework.
  6. Tensorflow supports which python version?
  7. Tensorflow supports which of the following platforms?
  8. Tensorflow is a symbolic math library based on .............
  9. There are ........... main tensor type you can create in TensorFlow.
  10. What is the Advantage of TensorFlow?
  11. What are the disadvantages of TensorFlow?
  12. What are the Features of TensorFlow?
  13. TensorFlow has only supported 64-bit Python 3.5.x or Python 3.6.x on Windows.
  14. TensorFlow managers handle the full lifecycle of Servables, except ..............
TensorFlow MCQ

Take TensorFlow MCQ Quiz & Online Test to Test your Knowledge

We have listed below the best TensorFlow MCQ Questions, that checks your basic knowledge of TensorFlow. This TensorFlow MCQ Test contains 20 multiple-choice questions. You have to select the right answer to every question to check your final preparation. apart from this, You can also download below the TensorFlow MCQ Pdf completely free.

  • Python
  • Java
  • PHP
  • Angular
  • IBM Team
  • Microsoft Team
  • Google Brain team
  • None of the above
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  • November 9, 2015
  • November 8, 2015
  • October 9, 2015
  • November 9, 2016
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  • C++
  • Python
  • CUDA
  • All of the above
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  • True
  • False
Download Free : TensorFlow MCQ PDF
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  • Python 3.0
  • Python 3.3
  • Python 3.5
  • Python 3.6–3.9
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  • Linux
  • macOS
  • Windows & Android
  • All of the above
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  • Dataflow
  • Differentiable programming
  • Both Dataflow & Differentiable programming
  • None of the above
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  • 2
  • 3
  • 4
  • 5
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  • It has excellent community support.
  • It is designed to use various backend software (GPUs, ASIC), etc. and also highly parallel.
  • It has a unique approach that allows monitoring the training progress of our models and tracking several metrics.
  • All of the above
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  • Missing Symbolic loops
  • No supports for windows
  • No GPU support for Nvidia
  • All of the above
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  • Flexible & Open Source
  • Easily Trainable & Layered Components
  • Open Source & Responsive Construct
  • All of the above
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  • Serving Servables
  • Metrics Servables
  • Loading Servables
  • Unloading Servables
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  • September 2019
  • October 2019
  • August 2019
  • November 2019
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  • Graphs are easy to plot
  • Calculations can be done in parallel
  • Tensors are nothing but computational graphs
  • All of the above
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  • We launch the graph in a session
  • A session is used to download the data
  • The current work space session for storing the code
  • A session is used for exporting data out of TensorFlow
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  • Scalar Dashboard
  • Histogram Dashboard
  • Distributer Dashboard
  • All of the above
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  • Keras
  • Azure
  • Python
  • PyTourch
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  • Yes
  • No
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