Algorithms

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Hashing is a technique used to uniquely identify a specific object from a group of similar objects. It involves mapping large data to fixed-size values.

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The N-Queens problem is a classic backtracking problem where the objective is to place N queens on an N×N chessboard such that no two queens threaten each other.

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Modular Exponentiation is an algorithm used to efficiently compute large powers modulo a number, using a technique called exponentiation by squaring.

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This post covers Dijkstra's Algorithm for finding the shortest paths in a graph, with code examples and explanations.

YOLO (You Only Look Once) is a popular deep learning algorithm for real-time object detection that divides images into grid cells and predicts bounding boxes and class probabilities for each cell.

Applications of Linked List in various fields including data structures, operating systems, and dynamic memory allocation.

Convolutional Neural Networks (CNNs) are specialized deep learning architectures that are particularly effective for image processing tasks due to their ability to capture spatial hierarchies in data.

Recurrent Neural Networks (RNNs) are a type of neural network designed to recognize patterns in sequences of data, including time-series data, language processing, and other sequence-related tasks.

Applications of Recursion in various fields, including algorithm design, problem-solving, and real-world use cases.

Computer Vision (CV) enables machines to interpret and understand visual data from the world. It is widely applied in tasks such as object detection, image classification, and facial recognition.

Definition

Generative Adversarial Networks (GANs) are a deep learning model that generate new data samples by training two neural networks in opposition. They are widely used in tasks such as image generation, style transfer, and data augmentation.

An overview of the Bellman-Ford algorithm, including its implementation in C++, Java, and Python, time complexity analysis, and comparison with Dijkstra's algorithm.

Definition

An overview of the Disjoint Set Union (Union Find) data structure, including implementations in C++, Java, and Python, complexity analysis, and applications.

Bloom Filters are probabilistic data structures used in applications where space efficiency is crucial, and approximate answers are acceptable, like database caching and network filtering.

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A comprehensive guide to Disjoint Set Union (DSU) with visual diagrams, Path Compression, Union by Rank optimizations, step-by-step dry-runs, code templates in Python, Java, and C++, and practice problems.

A comprehensive guide to Monotonic Stack and Monotonic Queue patterns with visual diagrams, step-by-step dry-runs, code templates in Python, Java, and C++, and practice problems.

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A comprehensive guide to Segment Trees with visual diagrams, build/query/update operations, lazy propagation, code templates in Python, Java, and C++, and practice problems.

A comprehensive guide to the Trie (Prefix Tree) data structure with visual diagrams, Insert, Search, Delete, and AutoComplete implementations in Python, Java, and C++, and practice problems.

A comprehensive guide to the Sliding Window algorithmic pattern with visual diagrams, step-by-step dry runs, code templates in Python, Java, and C++, and practice problems.