AI Practitioner

A heap is a binary tree-based data structure that satisfies the heap property: Min-Heap: Every parent node is less than or equal to its children. Max-Heap: Every parent node is greater than or equal to its children. **Heaps are not sorted, but they guarantee that the smallest (or largest) element is always at the top/root. 1. Visualizing a Heap (Min-Heap) Given input: [5, 3, 8, 1, 2] It turns into a binary tree like this: And stored in array like: [1, 2, 8, 5, 3] Each node at index i: Left child = index 2i + 1 Right child = index 2i + 2 2. Real-World Uses of Heaps 1) Priority queues 2) Scheduling systems 3) Dijkstra’s shortest path 4) Top K elements 5) Heap sort 3. Python Support: heapq Module Python’s built-in heapq module implements a Min-Heap by default. (To simulate a Max-Heap, just store negative numbers!) 4. Python Example: Min-Heap [min_heap.py] import heapq # Create a heap from a list nums = [ 5 , 3 , 8 , 1 , 2 ] heapq.heapify(nums) print( "Min-Heap:" , nums) # Th...