⚡Muhammed Elyamani's Projects
Data Structures & Algorithms Nanodegree Program from Udacity
ADAS Application with ROS2 using Camera and LIDAR using Gazebo Simulator.
AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
Project code for AI Programming with Python ND Program
Solving the inverse kinematics of a robotic arm is a necessary step whether it is a first-time installation or the configuration of the robotic arm is already changed. In this work, a machine learning-based approach for solving the inverse kinematic of a robotic arm with six degrees of freedom is presented.
An open autonomous driving platform
Easy & Modular Computer Vision Detectors and Trackers - Run YOLO-NAS,v8,v7,v6,v5,R,X in under 20 lines of code.
A collection of various awesome lists for hackers, pentesters and security researchers
A comprehensive list of papers using large language/multi-modal models for Robotics/RL, including papers, codes, and related websites
Handy algorithms
Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.
Open-source simulator for autonomous driving research.
Reverse engineered ChatGPT API
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5
Test 3 algorithms for classifying between dogs and not dogs
Code for the book "Mastering OpenCV with Practical Computer Vision Projects" by Packt Publishing 2012.
The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++
Cruise control in Simulink
Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent
Convolutional Neural Networks
YOLO ROS: Real-Time Object Detection for ROS
Handy Data Structures
Repo for the Deep Learning Nanodegree Foundations program.
Deep Object Pose Estimation (DOPE) – ROS inference (CoRL 2018)
Hello (Real) World with ROS – Robot Operating System course source file
DFS algorithm A standard DFS implementation puts each vertex of the graph into one of two categories: Visited Not Visited The purpose of the algorithm is to mark each vertex as visited while avoiding cycles. The DFS algorithm works as follows: Start by putting any one of the graph's vertices on top of a stack. Take the top item of the stack and add it to the visited list. Create a list of that vertex's adjacent nodes. Add the ones which aren't in the visited list to the top of stack. Keep repeating steps 2 and 3 until the stack is empty.
A toolkit for making real world machine learning and data analysis applications in C++
Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022