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Algorithms and Data structure, Introduction to algorithms, Algorithms for…
Algorithms and Data structure
Introduction to algorithms
1. Foundations
The role of algorithms in computing
Getting started
Growth of functions
Divide-and-conquer
Probabilistic analysis and randomized algorithms
2. Sorting and order statistics
Heapsort
Quicksort
Sorting in linear time
Medians and order statistics
3. Data structures
Elementary data structures
Hash table
Binary search trees
Red-black trees
Augmented data structures
4. Advanced design and analysis techniques
Dynamic programming
Greedy algorithms
Amortized analysis
5. Advanced data structures
B-Trees
Fibonacci Heaps
van Emde Boas trees
Data structures fro Disjoint sets
6. Graph algorithms
Elementary graph algorithms
Minimum spanning trees
Single-source shortest paths
All-pairs shortest paths
Maximum flow
7. Selected Topics
Multithreaded algorithms
Matrix operations
Linear programming
Polynomials and the FFT
Number-theoretic algorithms
String matching
Computational geometry
NP-completeness
Approximation algorithms
8. Appendix: Mathematical background
A. Summations
B. Sets, Etc.
C. Counting and probability
D. Matrices
Algorithms for dummies
Part 1. Getting started
Chapter 1. Introducing algorithms
Chapter 2. Considering algorithm design
Chapter 3. Using python to work with algorithms
Chapter 4. Introducing python for algorithm programming
Chapter 5. Performing essential data manipulations using python
Part 2. Understanding the need to sort and search
Chapter 6. Structuring data
Chapter 7. Arranging and searching data
Part 3. Exploring the world of graphs
Chapter 8. Understanding graph basics
Chapter 9. Reconnecting the dots
Chapter 10. Discovering graph secrets
Chapter 11. Getting the right web page
Part 4. Struggling with big data
Chapter 12. Managing big data
Chapter 13. Parallelizing operations
Chapter 14. Compressing data
Part 5. Challenging difficult problems
Chapter 15. Working with greedy algorithms
Chapter 16. Relying on dynamic programming
Chapter 17. Using randomized algorithms
Chapter 18. Performing local search
Chapter 19. Employing linear programming
Chapter 20. Considering heuristics
Part 6. The part of tens
Chapter 21. Ten algorithms that are changing the world
Chapter 22. Ten algorithmic problems yet to solve