4 dépôts
Pure Python codebases written for clarity and readability to teach internal algorithm logic.
Distinct from Pure Language Implementations: Distinct from general Pure Language Implementations: focuses specifically on the pedagogical use of pure Python for transparency.
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MLAlgorithms is an educational machine learning algorithm library consisting of core predictive models implemented from scratch in Python. It serves as a reference for developers to study the internal logic and mathematical workings of these models through clean, minimal implementations. The codebase focuses on the study of algorithm implementation and machine learning education, providing a way to understand internal mechanics by building components without relying on heavy external libraries. The project utilizes object-oriented encapsulation and NumPy-based vectorization to manage model s
Uses pure-Python logic to implement mathematical formulas, ensuring the internal workings are transparent and readable.
This project is a collection of foundational machine learning algorithms and tools implemented from scratch in Python. It serves as a library of core implementations for regression, classification, and clustering models, designed to demonstrate the underlying mathematical structures of these algorithms without relying on high-level machine learning frameworks. The project focuses on the manual implementation of algorithmic logic, including neural networks with forward propagation and weight updates, as well as various supervised and unsupervised learning models. It utilizes NumPy for vectoriz
Provides algorithmic implementations in pure Python to ensure the internal logic and mathematics are transparent and readable.
AlgorithmsByPython est une bibliothèque de référence et un dépôt éducatif fournissant des implémentations Python exécutables des fondamentaux de l'informatique. Il sert de guide complet pour les modèles algorithmiques, les structures de données fondamentales et les solutions pour la programmation compétitive et les défis d'entretiens techniques. Le projet se distingue en offrant un large éventail d'implémentations de référence, incluant un ensemble dédié de solutions pour les problèmes LeetCode courants. Il se concentre sur la traduction de la logique computationnelle théorique en code Python pratique pour un usage éducatif et pratique. Le dépôt couvre un large éventail de capacités, incluant la conception de collections linéaires, d'arbres et de graphes, ainsi que l'implémentation de stratégies de recherche et de tri. Il inclut des utilitaires pour la théorie des graphes, tels que les calculs de chemin le plus court et d'arbre couvrant minimal, et fournit des mécanismes pour l'indexation sur disque et la correspondance de motifs textuels.
Offers a collection of pure Python codebases designed to teach internal algorithm logic and data structure implementation.
Thonny is an educational integrated development environment designed for beginners learning Python programming. It serves as both a Python IDE and a microcontroller firmware editor, providing a simplified user interface for writing, testing, and debugging code. The environment focuses on Python programming education through graphical code debugging. It utilizes visual tools to illustrate program execution flow and variable states, allowing users to step through code to understand how logic and data change during runtime. The tool also supports microcontroller firmware development, enabling t
Provides a toolset that uses visual feedback and debugging to teach Python programming.