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Advanced Algorithms and Data Structures /
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 stru...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Shelter Island, NY :
Manning Publications,
[2021]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- 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. Multidimensional 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
- Appendix A. A quick guide to pseudo-code
- Appendix B. Big-O notation
- Appendix C. Core data structures
- Appendix D. Containers as priority queues
- Appendix E. Recursion
- Appendix F. Classification problems and randomnized algorithm metrics
- Index.