Algorithms: Advanced Data Structures for Algorithms

Are you studying data science and want to take your learning further ? Data structures are an integral part of <i>data science</i>, <i>machine learning</i>, and <b><i>algorithms</i></b>, all aimed at solving programming challenges that might seem insurmountable at the outset.<br><br><b><i>Advanced Data Structures for Algorithms</i></b> builds on your current knowledge, taking your learning much deeper and teaching you how to solve even the trickiest of challenges.<br><br><u>This book has been divided into four parts:</u><br><b>Part One covers advanced lists</b>, including:<br>• An overview of linked lists<br>• Doubly linked lists<br>• XOR linked lists<br>• Self-organizing lists<br>• Unrolled linked lists<br><b>Part Two covers trees</b>, including:<br>• Segment trees<br>• Trie trees<br>• Fenwick trees<br>• AVL trees<br>• Red-black trees<br>• Scapegoat trees<br>• Treap<br>• N-ary<br><b>Part Three discusses disjoint sets or Union-finds</b>, as they are sometimes known<br><b>Part Four covers heaps and priority queues</b>, including:<br>• A brief discussion on binary heaps<br>• Binomial heaps<br>• Fibonacci heaps<br>• Leftist heaps<br>• K-ary heaps<br>• Iterative heapsorts<br><br>You’ll find plenty of code examples to help you make sense of things and common-sense explanations.<br><br>If you want to advance your knowledge of data structures for algorithms you are in the right place.