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Showing 14 open source projects for "repository"
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1
Pythonic Data Structures and Algorithms
Minimal examples of data structures and algorithms in Python
The Pythonic Data Structures and Algorithms repository by keon is a hands-on collection of implementations of classical data structures and algorithms written in Python. It offers working, often well-commented code for many standard algorithmic problems — from sorting/searching to graph algorithms, dynamic programming, data structures, and more — making it a valuable resource for learning and reference. -
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PRML
PRML algorithms implemented in Python
PRML repository is a respected and well-maintained project that implements the foundational algorithms from the famous textbook Pattern Recognition and Machine Learning by Christopher M. Bishop, providing a practical and accessible Python reference for both students and professionals. Rather than just summarizing concepts, the repository includes working code that demonstrates linear regression and classification, kernel methods, neural networks, graphical models, mixture models with EM algorithms, approximate inference, and sequential data methods — all following the book’s structure and notation. ... -
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The Algorithms Python
All Algorithms implemented in Python
...The project covers various domains including mathematics, cryptography, machine learning, sorting, graph theory, and more. With contributions from a large global community, it continually grows and improves through collaboration and peer review. This repository is an ideal reference for students, educators, and developers seeking hands-on experience with algorithmic concepts in Python. -
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X's Recommendation Algorithm
Source code for the X Recommendation Algorithm
...It provides transparency into how tweets are selected, prioritized, and surfaced to users, reflecting Twitter’s move toward openness in recommendation algorithms. The repository contains the recommendation pipeline, which incorporates signals such as engagement, relevance, and content features, and demonstrates how they combine to form ranked outputs. Written primarily in Scala, it shows the architecture of large-scale recommendation systems, including candidate sourcing, ranking, and heuristics. While certain components (such as safety layers, spam detection, or private data) are excluded, the release provides valuable insights into the design of real-world machine learning–driven ranking systems. ... -
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All RL Algorithms from Scratch
Implementation of all RL algorithms in a simpler way
All RL Algorithms from Scratch is an educational reinforcement learning repository built around readable Python and Jupyter Notebook implementations. Its goal is to help learners understand how major reinforcement learning algorithms work under the hood instead of hiding the logic behind large frameworks. The project includes notebooks for value-based methods, policy-gradient methods, actor-critic algorithms, model-based learning, multi-agent reinforcement learning, planning, and hierarchical approaches. ... -
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Evolutionary Algorithm
Evolutionary Algorithm using Python
Evolutionary Algorithm is an educational Python project that demonstrates evolutionary computation techniques such as genetic algorithms, evolution strategies, and neuroevolution in a clear and accessible way. Rather than being a single monolithic library, this repository provides a series of self-contained examples showing how different population-based search methods solve optimization problems and adapt candidate solutions over generations. Users can explore basic genetic algorithm setups, match phrase examples, pathfinding challenges, and microbial GA variants, as well as evolution strategy approaches like NES. ... -
7
Real-ESRGAN
Real-ESRGAN aims at developing Practical Algorithms
...It extends the original Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) approach by training on synthetic degradations to make results more robust on real-world images, effectively enhancing resolution, reducing noise/artifacts, and reconstructing fine detail in low-quality imagery. The repository includes inference and training scripts, a model zoo with different pretrained models (including general and anime-oriented variants), and support for batch and arbitrary scaling, making it adaptable for diverse enhancement tasks. It emphasizes usability with utilities that handle alpha channels, gray/16-bit images, and tiled inference for large inputs, and can be run via Python scripts or portable executables. -
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AlphaTensor
AI discovers faster, efficient algorithms for matrix multiplication
...The project demonstrates how reinforcement learning can be used to automatically discover efficient algorithms for matrix multiplication — a fundamental operation in computer science and numerical computation. The repository is organized into four main components: algorithms, benchmarking, nonequivalence, and recombination. These contain implementations of the discovered matrix multiplication algorithms, tools to benchmark their real-world performance, proofs of nonequivalence among thousands of solutions, and methods for decomposing larger problems into smaller factorizations. ... -
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Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
...For each algorithm category, the repository pairs conceptual descriptions with runnable code and often illustrated exercises that help solidify understanding by bridging theory with practice. It’s structured to serve learners progressing from basic tabular methods to function approximation and deep learning extensions, making it suitable for students, researchers, or practitioners exploring reinforcement learning fundamentals. -
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10
TA-Lib.git: Technical Analysis Library
Mirror of the TA-Lib project using a Git repository
This project is intended to provide Git access to the code of the original project, TA-Lib, which uses Subversion. It is intended for system integrators wishing to use TA-Lib in their Git-managed project through Git submodules or subtrees. No actual development is being done here; all development happens in the original project. -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
Interactive Coding Challenges is a collection of practice problems designed to strengthen data structures, algorithms, and problem-solving skills. The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference solutions so you can compare approaches and learn idiomatic patterns. ... -
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MADDPG
Code for the MADDPG algorithm from a paper
MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in cooperative, competitive, and mixed settings. ... -
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Algorithms in Python
Data Structures and Algorithms in Python
...For anyone striving to move from “I know the syntax” to “I know how to use the right algorithm at the right time,” this repository is a practical asset. -
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pycrc
CRC C source generator
pycrc is an easy to use CRC (cyclic redundancy check) calculator and C source code generator. The generated source code can be optimized for simplicity, speed or space. pycrc contains a long parameter list of common CRC models. The program is self contained and does not require installation. Apart from a python installation, it does not require other libraries to be installed.
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