The 2019 Data Science Dictionary -- Key Terms You Need to Know

Activation function: In neural networks, linear and non-linear activation functions produce output decision boundaries by combining the network's weighted inputs. The ReLU (Rectified Linear Unit) activation function is the most commonly used activation function right now, although the Tanh or hyperbolic tangent, and Sigmoid or logistic activation functions are also used. Backpropagation: For this definition, I defer to a nice one I found by data scientist Mikio L. Braun on Quora: "Back prop is just gradient descent on individual errors. You compare the predictions of the neural network with the desired output and then compute the gradient of the errors with respect to the weights of the neural network. This gives you a direction in the parameter weight space in which the error would become smaller." Blockchain: Blockchain is essentially a decentralized distributed database.