Hands-On Generative Adversarial Networks with Keras

Artificial Neural Networks (ANNs)

Despite its recent success in many applications, deep learning is not new and according to Ian Goodfellow, Yoshua Bengio, and Aaron Courville, there have been three eras:

• Cybernetics between the 1940s and the 1960s
• Connectionism between the 1980s and the 1990s
• The current deep learning renaissance beginning in 2006

Mathematically speaking, a neural network is a graph consisting of non-linear equations whose parameters can be estimated using methods such as stochastic gradient descent and backpropagation. We will introduce ANNs step by step, starting with linear and logistic regression.

Linear regression is used to estimate the parameters of a model to describe the relationship between an output variable ...