Advanced algorithms and data structures - Rocca, Marcello La (Shelter Island, NY : Manning Publications, 2021)
Advanced Algorithms and Data Structures introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You'll discover cutting-edge approaches to a variety of tricky scenarios. You'll even learn to design your own data structures for projects that require a custom solution
1 Introducing data structures -- PART 1 IMPROVING OVER BASIC DATA STRUCTURES -- 2 Improving priority queues: d-way heaps -- 3 Treaps: Using randomization to balance binary search trees -- 4 Bloom filters: Reducing the memory for tracking content -- 5 Disjoint sets: Sub-linear time processing -- 6 Trie, radix trie: Efficient string search -- 7 Use case: LRU cache -- PART 2 MULTIDEMENSIONAL QUERIES -- 8 Nearest neighbors search -- 9 K-d trees: Multidimensional data indexing -- 10 Similarity Search Trees: Approximate nearest neighbors search for image retrieval -- 11 Applications of nearest neighbor search -- 12 Clustering -- 13 Parallel clustering: MapReduce and canopy clustering -- PART 3 PLANAR GRAPHS AND MINIMUM CROSSING NUMBER -- 14 An introduction to graphs: Finding paths of minimum distance -- 15 Graph embeddings and planarity: Drawing graphs with minimal edge intersections -- 16 Gradient descent: Optimization problems (not just) on graphs -- 17 Simulated annealing: Optimization beyond local minima -- 18 Genetic algorithms: Biologically inspired, fast-converging optimization.
Includes index.
Keywords: ALGORITHMS