As you explore many data structures and the algorithms and applications associated with them, you'll focus on the trade-offs between speed and storage and the benefits of deploying concurrency when appropriate. This book will demonstrate the huge increases in application performance that are possible. The presentation of classic data structures and techniques of algorithm design (greedy, divide and conquer, branch-and-bound to name a few) provides an essential foundation and toolkit for problem solving. But this book goes further by presenting heuristic algorithms and their implementations forsolving computationally intractable combinatoric optimization problems such as the travelling salesperson problem. Simulated annealing and genetic algorithms are among the techniques used.

The consistent style of coding used throughout this book exploits Go's ability to implement abstract, generic and constrained generic data types without the use of classes.  Although some familiarity with Go is assumed, this book should advance your ability to use Go to tackle server-side applications, games, machine learning, information retrieval and other application domains where speed and storage efficiency is essential.