The book provides the basic concepts and engineering applications of soft computing. Soft computing is the state-of-the-art approach to artificial intelligence, and mainly comprises fuzzy logic, neural networks and probabilistic reasoning techniques. It tries to imitate human reasoning particularly in computer environment. It deals with problems like imprecision, uncertainty and learning. Soft computing systems are adaptive and intelligent in nature and we may effortlessly construct systems and models which are simple applicable, user-friendly and fast with respect to computing. The book also focuses on fuzzy logic and neural networks and areas related to soft computing. The book discusses:  Basics of soft computing, its importance and applications in various fields with suitable examples. Use, applications, advantages and disadvantages of neural network and its comparison with similar techniques.  Basic concepts of supervised learning, its applications and comparison with similar technologies. Advantages of unsupervised learning, its comparison with similar technologies and various applications like SOM Boltzman machine, Hopfield network, etc. Concepts of genetic algorithm and its applications. Concepts of fuzzy logic, its comparison with similar techniques, dynamic properties as well as the internal structure of the fuzzy rules.