dynamic programming

Solving the subset sum problem (SSP) via dynamic programming

Python dice probability package.

Source code of the model Chevalier et al (2020) Am Nat

This project adopts Reinforcement Learning to solve a variant of the stochastic VRP, where customers are highly variable, demands are stochastic, and vehicles have a duration limit.

Study of execution time of differents algorithms to solve the knapsack problem, in differents instances of the problem created with a generator of knapsack problem.

This package is an attempt to make it easy to render paragraphs to a PIL Image in Python, with excellent line-breaking via the Knuth-Plass algorithm (commonly known as the TeX/LaTeX line-breaking algorithm). A simple greedy wrapping algorithm is available as a fallback. Console/text output is supported as well as PIL output.

This project is meant to master Dynamic Programming, by breaking it down into a collection of simpler subproblems, solving each of those subproblems just once, and storing their solutions using a memory-based data structure.

Gutenberg is a pipeline for training a neural network in segmenting and recognising frequent words in early printed books, in particular we focus on Gutenberg’s Bible.

Algorithms and Data Structure Implemented in C++

Preparations for coding interviews