A Gentle Introduction To Neural Networks Series -- Part 1

Neural networks and deep learning are big topics in Computer Science and in the technology industry, they currently provide the best solutions to many problems in image recognition, speech recognition and natural language processing. Recently many papers have been published featuring AI that can learn to paint, build 3D Models, create user interfaces(pix2code), some create images given a sentence and there are many more incredible things being done everyday using neural networks. I'm writing this series of posts about Neural Networks and Deep learning, where I'm going to guide you from learning the basic concepts of Artificial Neural Networks (ANN), show you examples from simple Network to mimic the AND gate, to solving Image recognition tasks using Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNN) and more. The code will always be written in python, some times with the help of Tensorflow (I don't expect you to be guru using Tensorflow as I will try to explain the code in details). The definition of a neural network, more properly referred to as an'artificial' neural network (ANN), is provided by the inventor of one of the first neurocomputers, Dr. Robert Hecht-Nielsen.