"Need help getting started with Genetic Algorithms, Neural Networks or Swarm Intelligence? Clever Algorithms: Nature-Inspired Programming Recipes Nature-Inspired Algorithms are Fascinating! But implementing them can be frustrating. The algorithm descriptions are incomplete, inconsistent and distributed across academic papers, websites and code. There are so many algorithms to choose from, it can feel overwhelming. Get An Algorithms Handbook You need a handbook of algorithm recipes! Each algorithm is described in a consistent and structured way with a working code example. You need Clever Algorithms: Nature-Inspired Programming Recipes. Clever Algorithms is a handbook of recipes for computational problem solving. Algorithms in the book are drawn from sub-fields of Artificial Intelligence such as Computational Intelligence, Biologically Inspired Computation, and Metaheuristics. This 438-page PDF ebook contains... ...45 algorithm descriptions ...best practice usage heuristics for each algorithm ...pseudo-code listing of each algorithm ...code listings of each algorithm in Ruby (source code files included) ...references for further reading including the primary sources for each algorithm 45 Algorithm Descriptions The book includes an introduction to artificial intelligence and related fields as well as advanced topics like algorithm testing and visualization. The 45 algorithms are grouped into chapters, as follows: Stochastic Algorithms: Random Search, Adaptive Random Search, Stochastic Hill Climbing, Iterated Local Search, Guided Local Search, Variable Neighborhood Search, GRASP, Scatter Search, Tabu Search and Reactive Tabu Search. Evolutionary Algorithms: Genetic Algorithm, Genetic Programming, Evolution Strategies, Differential Evolution, Evolutionary Programming, Grammatical Evolution, Gene Expression Programming, Learning Classifier System, NSGA and SPEA. Physical Algorithms: Simulated Annealing, Extremal Optimization, Harmony Search, Cultural Algorithm and the Memetic Algorithm Probabilistic Algorithms: PIBL, UMDA, Compact Genetic Algorithm, Bayesian Optimization Algorithm and the Cross-Entropy Method. Swarm Algorithms: Particle Swarm Optimization, Ant System, Ant Colony Optimization, Bees Algorithm and the Bacterial Foraging Optimization Algorithm. Immune Algorithms: Clonal Selection Algorithm, Negative Selection Algorithm, Artificial Immune Recognition System, Immune Network Algorithm and the Dendritic Cell Algorithm. Neural Algorithms: Perceptron, Back-Propagation, Hopfield Network, Learning Vector Quantization and the Self-Organizing Map. All algorithm descriptions include a working implementation of the algorithm in Ruby. The standalone ruby files for each algorithm are also included in your download." #books #ruby #algorithms #machine_learning #data_science #paid #ebooks #price:$17 #freemium #free #lists #pub