The idea is that TensorFlow works at a relatively low level and coding directly with TensorFlow is very challenging. Put another way, you write Keras code using Python. The Keras code calls into the ...

The demo program is named mnist_cnn.py and it starts by importing the NumPy, Keras, TensorFlow, OS and PyPlot packages. You don't need to explicitly import TensorFlow, but the demo program does so ...

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 ...

Even in TensorFlow 1.12, the official Get Started with TensorFlow tutorial uses the high-level Keras API embedded in TensorFlow, tf.keras.By contrast, the TensorFlow Core API requires working with ...

TensorFlow 2.0 comes with a number of changes made in an attempt to improve ease of use, such as the elimination of some APIs thought to be redundant and a tight integration and reliance on tf ...