Solutions to problems found in Elements of programming interviews book

Apprendre le langage Kotlin en résolvant les problèmes de advent-of-code 2016.

Apprendre Kotlin en résolvant les problèmes de advent of code 2018

Collection of solutions for algorithm problems from Codility and other sources in Kotlin.

A collection of data structures and algorithms in various languages for practicing purposes

Playground to play with algorithm

Learning Kotlin lang while solving hackerrank challenges

Penerapan Weighted PRNG dengan studi kasus Gacha pada game Genshin Impact

Base algorithms implementations, base data structure implementations, Leetcode problems solutions

Coding test template for kotlin developers

Kotlin solutions of the LeetCode Top Interview Questions.

Approximation algorithms are algorithms that find approximate solutions to optimization problems, usually with a guarantee of the solution's quality relative to the optimal solution. They are used when exact solutions are too time-consuming to compute. Approximation algorithms trade-off optimality for efficiency and are commonly used in scheduling.

Backtracking algorithms solve problems by trying out solutions incrementally and undoing them if they lead to a dead end. It is a systematic method of trying out different solutions to a problem by incrementally building a solution and undoing it if it leads to an invalid state. It is commonly used in solving problems such as the n-queens problem.

Backtracking algorithms solve problems by trying out solutions incrementally and undoing them if they lead to a dead end. It is a systematic method of trying out different solutions to a problem by incrementally building a solution and undoing it if it leads to an invalid state.

The Boyer-Moore algorithm is a string search algorithm that efficiently searches for the occurrence of a pattern in a text. It works by pre-processing the pattern to determine the bad character rule and good suffix rule, which are used to quickly skip over sections of the text that cannot match the pattern. Time complexity of O(n/m)

The Knuth-Morris-Pratt (KMP) algorithm is a linear time pattern matching algorithm that efficiently searches for occurrences of a pattern in a text. It pre-processes the pattern to determine a partial match table which is used to quickly skip over sections of the text that cannot match the pattern.

.A Generative Adversarial Network (GAN) is a deep learning architecture used to generate new data that resembles existing data. It consists of two neural networks, a generator and a discriminator, that are trained in competition with each other. The generator creates synthetic data, while the discriminator tries to distinguish between real.

Deep Reinforcement Learning is a subfield of machine learning where an agent learns to make decisions in an environment through trial and error, with feedback in the form of rewards or penalties. It has applications in robotics, game AI, and decision making.