Neural Network Primitives Part 1 - McCulloch Pitts Neuron Model (1943) Machine Learning Knowledge

Modern machine learning world is going crazy over deep learning. People are stacking hundreds and thousands of interconnected artificial neurons to build the most complex of deep neural network than ever. These deep neural nets are able to create the most astonishing AIs that are outperforming humans in many tasks. But just like complex living forms, which evolved from the primitive cellular life, even the deep neural network had its humble beginning as a primitive artificial neuron dating back to McCulloch-Pitts Neuron Model in 1943. Neural Network Primitives is a series to understand the primitive forms of the artificial neural networks and how these were the first building blocks of modern deep learning.