Development of ML models using TensorFlow

TensorFlow is a machine learning framework that performs high-performance numerical computations. TensorFlow owes its popularity to its high quality and vast amount of documentation, its ability to easily serve models at scale in production environments, and the friendly interface to GPUs and TPUs.

TensorFlow, to facilitate the development and deployment of ML models, has many high-level APIs, including Keras, Eager Execution, and Estimators. These APIs are very useful in many contexts, but, in order to develop RL algorithms, we'll only use low-level APIs.

Now, let's code immediately using TensorFlow. The following lines of code execute the sum of the constants, a and b, created with tf.constant():

import tensorflow as tf

# create two constants: a and b
a = tf.constant(4)
b = tf.constant(3)

# perform a computation
c = a + b

# create...