from tensorflow.python.framework import tensor_shape from tensorflow.python.platform import tf_logging as logging from tensorflow.python.util import _pywrap_utils ...

TensorFlow 2.0, released in October 2019, revamped the framework significantly based on user feedback. The result is a machine learning framework that is easier to work with—for example, by ...

This is an extensive library of my notes on this section of the course, covering the fundamental aspects of TensorFlow with Python. This includes essential topics on machine learning, neural networks, ...

TensorFlow is a free and open source library that is available for Python, JavaScript, C++, and Java. This flexibility lends itself to a wide range of applications in many different sectors.

For these cases, PyTorch and TensorFlow can be quite effective, especially if there is already a trained model similar to what you need in the framework’s model library. PyTorch ...

The library supports both the TensorFlow and Theano backends, which makes it a great choice for those who don’t want to get too involved with TensorFlow. The open-source library provides you with all ...