TensorFlow requirements

TensorFlow requirements

  • Development phase:- when you are coding and training a neural network.
  • Runtime(or inference) phase:- when you are making predictions with a trained neural network.
  • Development phase requirements:- windows, macOS, or Linux
    can use multiple Linux computer(locally or in the cloud ) for very large projects.
  • Runtime phase supports:- computers running Windows, macOS or Linux.Linux servers running TensorFlow serving. google's cloud machine learning engine service. IOS or Android mobile apps.

GPU acceleration

Tensorflow can take advantage of NVIDIA-brand GPUs.
GPUs can greatly decrease neural network training times for large neural networks.
Using a GPU with TensorFlow requires installing additional software from NVIDIA(CUDA and cuDNN).


Programming language support

TensorFlow's core execution is written in c++ for speed. Python is the best supported and easiest language to use with TensorFlow.

Supervised learning

The branch of machine learning where the computer learn how to perform a function by looking at labelled training data.

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