It’s not necessary to import all of the Keras and Tensorflow library functions. # Begin a Keras script by importing the Keras library: Once TensorFlow and Keras are installed, you can start working with them. For information about Matplotlib and how to install it, refer to What is Matplotlib in Python? How to Import Keras and TensorFlow If you intend to create plots based on TensorFlow and Keras data, then consider installing Matplotlib. Requires: google-pasta, gast, six, protobuf, tensorboard, h5py, termcolor, absl-py, opt-einsum, wrapt, grpcio, keras-preprocessing, tensorflow-estimator, numpy, astunparse, wheel, scipy Summary: TensorFlow is an open source machine learning framework for everyone. Output should be similar to: Name: tensorflow You can verify the TensorFlow installation with the following command: python -m pip show tensorflow If you already have TensorFlow and Keras installed, they can be updated by running the following command: pip install -U tensorflow └── wrapt~=1.12.1 Update Tensorflow and Keras Using Pip The installation installs a slew of TensorFlow and Keras dependencies: tensorflow If you’re working with Deep Neural Networks, you’ll should also install the latest version of the cuDNN library.Install v11 or later of the CUDA® Toolkit.Ensure you’re running a CUDA®-enabled card.For AMD GPUs, refer to the article Install Tensorflow 2 for AMD GPUs.If you want to use your GPU to the training, you’ll need to do the following: If you’re fine with using the CPU to train your neural network, your installation is done. To install TensorFlow for CPU and GPU processors, run the following command: pip install tensorflow Run the following command to ensure that the latest version of pip is installed: pip install -upgrade pip Output should be similar to: Python 3.8.2 You can determine the version of Python installed on your computer by running the following command: python3 -version TensorFlow and Keras require Python 3.6+ (Python 3.8 requires TensorFlow 2.2+), and the latest version of pip. GPU – most high end computers feature a separate Graphics Processing Unit (GPU) from Nvidia or AMD that offer training speeds much faster than CPUs, but not as fast as TPUs.
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