The basics of artificial neural networks (ANN), applications, and implementation, are examined. The book targets multidisciplinary audience and explains the principles of neural networks in the simplest terminology. With the advent of computer software platforms in the market, no previous high level mathematical skills are required to implement an ANN project, except for basic algebra skills, and calculus. The book is also essential for industry professionals seeking to improve their production processes. Luckily with ANN, models and even complete software can be built with available data of a process, machine, business activity, or a natural phenomenon. The two important observations about neural networks are: data quantity is as important as the data quality. You need enough data that will allow the network to 'learn'. Secondly, neural networks are 'black box' models and can replace 'traditional' programming, but not the human brain; you still need to interpret the results. The book is therefore an eye opener for curious readers on the current paradigm shift from 'traditional' programming to a versatile, efficient world of algorithms in tackling most of the 21st century problems.