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Related lectures (27)

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Introduction to Algorithms: Basics and Importance

Covers the basics of algorithms, the importance of studying them, data structures, and the impact of algorithms on various fields.

Computation & Algorithms II: Binary Search and Merge Sort

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

Search Algorithms: Two Examples

Covers basic algorithm ingredients, search algorithms, control structures, and algorithm correctness.

Hashing & Sorting

Explores hashing techniques like static, extendible, and linear hashing, along with sorting methods such as external merge sort and B+ trees.

Merge Sort: Sorting Algorithm

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

Complexity & Induction: Algorithms & Proofs

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

Data-Driven Modeling of Haemodynamics in Vascular Flows

Explores data-driven modeling of haemodynamics in vascular flows, focusing on computational challenges, reduced order modeling, FSI problems, and neural network applications.

Matrix Factorization: Optimization and Evaluation

Explores matrix factorization optimization, evaluation methods, and challenges in recommendation systems.

Algorithmic Challenges: Solutions and Optimization

Explores algorithmic challenges, time complexity, optimization, recursion, and probability calculations.

Gradient Descent

Covers the concept of gradient descent, a universal algorithm used to find the minimum of a function.