Search Results for "ns2 code with algorithm"
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142 projects for "ns2 code with algorithm" with 1 filter applied:
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how-to-optim-algorithm-in-cuda
How to optimize some algorithm in cuda
how-to-optim-algorithm-in-cuda is an open educational repository focused on teaching developers how to optimize algorithms for high-performance execution on GPUs using CUDA. The project combines technical notes, code examples, and practical experiments that demonstrate how common computational kernels can be optimized to improve speed and memory efficiency. -
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X For You Feed Algorithm
Algorithm powering the For You feed on X
X For You Feed Algorithm is the open-sourced core recommendation system that powers the For You feed on X (the social network formerly known as Twitter), and it represents one of the first times a major social platform has published production-level ranking code for public review and experimentation. The repository contains the full pipeline that ingests user engagement and content candidate data, processes it through retrieval, hydration, filtering, scoring, and selection layers, and ultimately ranks posts to show what appears in a user’s feed. ... -
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ML-NLP
This project is a common knowledge point and code implementation
ML-NLP is a large open-source repository that collects theoretical knowledge, practical explanations, and code examples related to machine learning, deep learning, and natural language processing. The project is designed primarily as a learning resource for algorithm engineers and students preparing for technical interviews in machine learning or NLP roles. It compiles important concepts that frequently appear in machine learning discussions, including neural network architectures, training methods, and common algorithmic techniques. ... -
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LeetCode Animation
Demonstrate all the questions on LeetCode in the form of animation
LeetCodeAnimation is an educational open source project by MisterBooo that visually demonstrates algorithm problems from LeetCode through animations. The goal of the project is to help learners understand complex algorithmic concepts intuitively by showing step-by-step animated explanations instead of relying solely on static code or text. Each animation corresponds to a specific problem and illustrates how data structures and algorithms operate dynamically, making it easier to grasp their underlying logic. ... -
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AIDE ML
AI-Driven Exploration in the Space of Code
AIDE ML is an open-source research framework designed to explore automated machine learning development through agent-based search and code optimization. The project implements the AIDE algorithm, which uses a tree-search strategy guided by large language models to iteratively generate, evaluate, and refine code. Instead of relying on manual experimentation, the agent autonomously drafts machine learning pipelines, debugs errors, and benchmarks performance against user-defined evaluation metrics. ... -
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go-algorithms
Algorithms and data structures for golang
...It includes a wide range of classic sorting, searching, and numerical algorithms alongside basic collection structures such as stacks, queues, linked lists, and binary trees. The repository is organized into clear directories by topic, making it easy for learners to explore specific categories of algorithms. Because the code focuses on clarity over heavy abstraction, it is especially useful for students and developers studying algorithmic fundamentals. Overall, go-algorithms serves as a practical reference and study companion for Go programmers building a strong foundation in data structures and algorithm design. -
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Pythonic Data Structures and Algorithms
Minimal examples of data structures and algorithms in Python
...Because it’s in pure Python, it’s easy to read and modify, making it accessible even to those with modest programming experience. The repo helps bridge the gap between theoretical algorithm descriptions and real-world code, giving concrete, working implementations that one can study, debug, or extend. -
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recipes
Some code snippets for sharing
Recipes is a long-running collection of reusable programming snippets and small experiments rather than a single software package. The repository groups examples by topic so developers can inspect isolated implementations and techniques. Its directories cover algorithms, basic utilities, benchmarking, date and time handling, hashing, sorting, networking, and logging. Other examples explore Protocol Buffers, RPC, reactors, SSL, strings, threading, and top-k processing. Java and Python... -
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LeetCode Book
Comprehensive study guide for coding interviews
LeetCode-Book is a comprehensive study guide for coding interviews that consolidates algorithm patterns, data-structure templates, and worked LeetCode solutions. It organizes problems by topic—arrays, linked lists, stacks/queues, trees/graphs, dynamic programming, greedy, backtracking, and math—so you can study systematically. Explanations are concise but intentional, highlighting why a pattern fits, how to reason about boundary cases, and the time/space trade-offs. -
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ML for Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
ML-For-Beginners is a structured, project-driven curriculum that teaches foundational machine learning concepts with approachable math and lots of code. Organized as a multi-week course, it mixes short lectures with labs in notebooks so learners practice regression, classification, clustering, and recommendation techniques on real datasets. Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs. ... -
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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... -
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D4RL
Collection of reference environments, offline reinforcement learning
D4RL (Datasets for Deep Data-Driven Reinforcement Learning) is a benchmark suite focused on offline reinforcement learning — i.e., learning policies from fixed datasets rather than via online interaction with the environment. It contains standardized environments, tasks and datasets (observations, actions, rewards, terminals) aimed at enabling reproducible research in offline RL. Researchers can load a dataset for a given task (e.g., maze navigation, manipulation) and apply their algorithm... -
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RL with PyTorch
Clean, Robust, and Unified PyTorch implementation
RL with PyTorch is a research-oriented repository that provides implementations of deep reinforcement learning algorithms using the PyTorch framework. The project focuses on helping developers and researchers understand reinforcement learning methods by providing clean and reproducible implementations of well-known algorithms. It includes code for popular deep reinforcement learning techniques such as Deep Q-Networks, policy gradient methods, actor-critic architectures, and other modern RL... -
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machine-learning-refined
Master the fundamentals of machine learning, deep learning
machine-learning-refined is an educational repository designed to help students and practitioners understand machine learning algorithms through intuitive explanations and interactive examples. The project accompanies a series of textbooks and teaching materials that focus on making machine learning concepts accessible through visual demonstrations and simple code implementations. Instead of presenting algorithms purely through mathematical derivations, the repository emphasizes geometric... -
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pytudes
Python programs, usually short, of considerable difficulty
pytudes is Peter Norvig’s collection of short Python programs written to practice and demonstrate specific programming skills. The name is inspired by musical études, meaning compact exercises designed to build mastery through focused practice. The repository includes readable solutions, experiments, notebooks, and scripts that cover algorithms, puzzles, probability, search, language processing, simulation, and mathematical reasoning. It is useful for programmers who want to study elegant... -
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Machine learning algorithms
Minimal and clean examples of machine learning algorithms
Machine learning algorithms is an open-source repository that provides minimal and clean implementations of machine learning algorithms written primarily in Python. The project focuses on demonstrating how fundamental machine learning methods work internally by implementing them from scratch rather than relying on high-level libraries. This approach allows learners to study the mathematical and algorithmic details behind widely used models in a transparent and readable way. The repository... -
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YAPF
A formatter for Python files
YAPF is a Python code formatter that automatically rewrites source to match a chosen style, using a clang-format–inspired algorithm to search for the “best” layout under your rules. Instead of relying on a fixed set of heuristics, it explores formatting decisions and chooses the lowest-cost result, aiming to produce code a human would write when following a style guide. -
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deep-q-learning
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
The deep-q-learning repository authored by keon provides a Python-based implementation of the Deep Q-Learning algorithm — a cornerstone method in reinforcement learning. It implements the core logic needed to train an agent using Q-learning with neural networks (i.e. approximating Q-values via deep nets), setting up environment interaction loops, experience replay, network updates, and policy behavior. For learners and researchers interested in reinforcement learning, this repo offers a concrete, runnable example bridging theory and practice: you can execute the code, play with hyperparameters, observe convergence behavior, and see how deep Q-learning learns policies over time in standard environments. ... -
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Go Katas
A collection of daily coding challenges
...Because Go is widely used for backend services, cloud tooling, and systems programming, this repository helps participants build confidence in writing reliable, idiomatic, and maintainable code in real environments. -
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International Components for Unicode
The home of the ICU project source code
ICU is a mature, widely used set of C/C++ and Java libraries providing Unicode and Globalization support for software applications. ICU is widely portable and gives applications the same results on all platforms and between C/C++ and Java software. ICU is released under a nonrestrictive open-source license that is suitable for use with both commercial software and with other open-source or free software. Convert text data to or from Unicode and nearly any other character set or encoding.... -
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AI-Job-Notes
AI algorithm position job search strategy
AI-Job-Notes is a pragmatic notebook for landing roles in machine learning, computer vision, and related engineering tracks. It assembles study paths, checklists, and interview prep materials, but also covers job-search mechanics—portfolio building, resume patterns, and communication tips. The emphasis is on doing: practicing with project ideas, setting up reproducible experiments, and showcasing results that convey impact. It ties technical study (ML/DL fundamentals) to real hiring signals... -
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shadowsocks-libev
Bug-fix-only libev port of shadowsocks
Shadowsocks-libev is a lightweight secured SOCKS5 proxy for embedded devices and low-end boxes. Shadowsocks-libev is written in pure C and depends on libev. It's designed to be a lightweight implementation of shadowsocks protocol, in order to keep the resource usage as low as possible. Snap is the recommended way to install the latest binaries. You can build shadowsocks-libev and all its dependencies by script. The latest shadowsocks-libev has provided a redir mode. You can configure your... -
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cline
Command line tool for counting source code lines
cline is a command line tool that counts code lines or non-whitespace characters in your project folder. It is designed to recursively find any source file matching specific rules and count the line breaks within that file. You may specify file suffixes to include or exclude as well as regular expressions for code lines that shall be excluded (e.g. to exclude comments). By default a heuristic algorithm skips binary files. -
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Nyquist
Nyquist is a language for sound synthesis and music composition.
Nyquist is a language for sound synthesis and music composition. It is implemented in C and C++ and runs on Win32, OSX, and Linux. Nyquist combines a powerful functional programming style with efficient signal-processing primitives. Nyquist is also embedded as a scripting language in Audacity. -
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cfMesh
A library for polyhedral mesh generation
...It is already a part of foam-extend, OpenFOAM for Windows, Caelus and OpenFOAM+ released by ESI. This repository is intended for contribution and collaborative development. If you have a new meshing algorithm or interested in contributing to cfMesh, do not hesitate to contact us. Please note that this code is not the same as CF-MESH+, which is a commercial product offered by Creative Fields Holding.
