Are you studying data science and want to take your learning further ? Data structures are an integral part of data science, machine learning, and algorithms, all aimed at solving programming challenges that might seem insurmountable at the outset.

Advanced Data Structures for Algorithms builds on your current knowledge, taking your learning much deeper and teaching you how to solve even the trickiest of challenges.

This book has been divided into four parts:

Part One covers advanced lists, including:

- An overview of linked lists

- Doubly linked lists

- XOR linked lists

- Self-organizing lists

- Unrolled linked lists

Part Two covers trees, including:

- Segment trees

- Trie trees

- Fenwick trees

- AVL trees

- Red-black trees

- Scapegoat trees

- Treap

- N-ary

Part Three discusses disjoint sets or Union-finds, as they are sometimes known

Part Four covers heaps and priority queues, including:

- A brief discussion on binary heaps

- Binomial heaps

- Fibonacci heaps

- Leftist heaps

- K-ary heaps

- Iterative heapsorts

You'll find plenty of code examples to help you make sense of things and common-sense explanations.

If you want to advance your knowledge of data structures for algorithms you are in the right place.