
Comprehensive playlist covering essential data structures, from arrays to advanced trees, with implementation details and algorithmic applications.

Explore the fundamentals and advanced concepts of Gradient Boost for regression and classification in machine learning.

Learn about priority queues, including min/max heaps, insertion, removal, and implementation, to enhance your data structure knowledge and coding skills.

Explore cutting-edge algorithms for software-defined networking with experts. Topics include control plane analysis, network monitoring, traffic engineering, and packet scheduling in high-speed networks.

The course discusses efficient algorithms from a large number of domains. This course assumes the knowledge of data structures, the knowledge big-O notation and the concept of time and space complexity of an algorithm.

This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems.

Comprehensive exploration of optimization techniques, covering linear and nonlinear programming, integer programming, transportation problems, and multi-objective decision making.

Explore concept maps in C++23, using inline variable templates to achieve benefits similar to C++0x Concepts. Learn advanced techniques for implementing flexible data structures with monoid-based tags.

Learn to implement and traverse Binary Trees and Binary Search Trees in Python, covering creation algorithms, traversal methods, and their advantages and disadvantages.

Learn Java search algorithms: linear and binary search implementation, time and space complexity analysis, and algorithmic concepts for optimized data retrieval.

Learn to implement and analyze Selection Sort in Java, covering its logic, implementation, time complexity, and practical applications.

Comprehensive exploration of data structures and algorithms using Python, covering fundamental concepts, implementation, and analysis for beginners to enhance problem-solving skills.

Learn Prim's Algorithm for finding minimal spanning trees using Java, covering greedy programming concepts and practical implementation with detailed explanations and code examples.

Master essential data structures in Java: arrays, stacks, queues, linked lists, trees, graphs, and hash tables. Gain practical implementation skills and understand their applications and trade-offs.

Explore BFS and DFS algorithms for graph traversal in Java, covering their concepts, implementation, and practical applications in computer science and programming.

Learn graph data structures in Java, including types, representations, and traversal algorithms like BFS and DFS. Gain practical implementation skills for efficient graph manipulation.

Comprehensive exploration of data structures and algorithms in Java, covering fundamental concepts, implementation, and analysis of various techniques for efficient programming and problem-solving.

Explore stochastic gradient descent, its advantages, and implementation. Learn about mini-batches, momentum, and convergence in this optimization algorithm for machine learning models.

Learn the QuickSort algorithm in C, including its implementation, time and space complexity, and practical examples. Gain a deep understanding of this efficient sorting technique.

Learn to implement and analyze the Insertion Sort algorithm in C, covering its algorithm, demonstration, time and space complexity, with practical examples and step-by-step explanations.

Great Learning brings you this video “Merge Sort Algorithm”, aimed at helping you understand this specific type of algorithm. This video will help you understand the implementation of Merge sort algorithms and its analysis.