Lectures related to Binary Search Algorithm

Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Provides an overview of essential search and sort algorithms in computer science.

Explores worst-case complexity, mathematical induction, and algorithms like binary search and insertion sort.

Explores dynamic programming for palindromic subsequences, merging binary search trees, and finding the median of two sorted arrays.

Covers the complexity analyses of algorithms and their worst-case time complexities.

Explores sorting and recursive algorithms, including complexity analysis, maximal value, and binary search.

Introduces recursion and binary search algorithms for efficient problem-solving.

Explains binary search, the logarithm function, and recursive algorithms for factorial and Fibonacci sequences.

Explains the binary search algorithm using two pointers to efficiently search a sorted list.

Covers the time complexity of algorithms and includes a quiz.

Covers the complexity analyses of search and sorting algorithms.

Covers algorithms for searching, sorting, optimization, and the Halting Problem.

Covers the binary search algorithm and provides a step-by-step example.

Covers recursion, dynamic programming, and algorithm design using divide and conquer strategies.

Explores algorithm growth, search complexities, and logarithmic properties in depth, with practical exercises included.

Explores optimization problems and greedy algorithms for efficient decision-making.

Explores binary search, merge sort, recursion in algorithms, Fibonacci numbers, and dynamic programming.

Explores binary search fundamentals, efficiency, and temporal complexity in algorithmic searching.

Covers the introduction to logarithms, algorithmic notations, and analysis of algorithm travel times.

Explains the merge sort algorithm, its correctness, and time complexity compared to other sorting algorithms.