222 skills found · Page 7 of 8
trololollo78 / Prompt Engineering🚀 Master prompt engineering to optimize AI interactions with guides, examples, and best practices for all skill levels and domains.
OmarEssameldinMousa / Real World Software Engineering LabsThis repository offers a collection of hands-on labs designed to simulate real-world production issues. Sharpen your skills in debugging, refactoring, pipeline optimization, and performance tuning with challenges that mirror what you'd encounter in a professional software engineering environment.
PkLavc / Os Resource OptimizerA systems engineering simulator designed to optimize CPU scheduling and memory allocation. Built in C++, it demonstrates low-level resource management, algorithmic efficiency, and operating system principles. Focused on high-performance computing and hardware-software co-design.
mriusero / Predictive Maintenance On Industrial RobotsThis project develops predictive maintenance models for industrial robots in nuclear fuel replacement, leveraging data analytics, machine learning, and decision-making frameworks to optimize robot fleet management and extend operational uptime. Key phases include data exploration, feature engineering, RUL prediction, and maintenance decision-making
tonywang07009 / C Industrial IoT Sensor System Simple This project simulates a factory's digital transformation using IoT sensors and a statistical analysis DLL. By identifying bottlenecks with low availability or long cycle times, the system applies Industrial Engineering Line Balancing techniques. It recommends machine adjustments to optimize utilization rates and balance Takt time effectively.
ayazhassan / RT CUDA GUI DevelopmentRecent development in Graphic Processing Units (GPUs) has opened a new challenge in harnessing their computing power as a new general-purpose computing paradigm with its CUDA parallel programming. However, porting applications to CUDA remains a challenge to average programmers. We have developed a restructuring software compiler (RT-CUDA) with best possible kernel optimizations to bridge the gap between high-level languages and the machine dependent CUDA environment. RT-CUDA is based upon a set of compiler optimizations. RT-CUDA takes a C-like program and convert it into an optimized CUDA kernel with user directives in a con.figuration .file for guiding the compiler. While the invocation of external libraries is not possible with OpenACC commercial compiler, RT-CUDA allows transparent invocation of the most optimized external math libraries like cuSparse and cuBLAS. For this, RT-CUDA uses interfacing APIs, error handling interpretation, and user transparent programming. This enables efficient design of linear algebra solvers (LAS). Evaluation of RT-CUDA has been performed on Tesla K20c GPU with a variety of basic linear algebra operators (M+, MM, MV, VV, etc.) as well as the programming of solvers of systems of linear equations like Jacobi and Conjugate Gradient. We obtained significant speedup over other compilers like OpenACC and GPGPU compilers. RT-CUDA facilitates the design of efficient parallel software for developing parallel simulators (reservoir simulators, molecular dynamics, etc.) which are critical for Oil & Gas industry. We expect RT-CUDA to be needed by many industries dealing with science and engineering simulation on massively parallel computers like NVIDIA GPUs.
AdilShamim8 / Prompt EngineeringA repository dedicated to mastering prompt engineering with curated guides, examples, and best practices for optimizing AI interactions.
tfenz / TE SR WAN SimulationTraffic Engineering with Joint Link Weight and Segment Optimization
snrdevs / Particle Swarm OptimizationParticle Swarm Optimization Algorithm implementation for engineering problems
ZongSingHuang / Multi Strategy Enhanced Whale Optimization AlgorithmZ. Huang and W. Li, "Novel Multi-Strategy Enhanced Whale Optimization Algorithm", 2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE), 2020.
john-data-chen / Turborepo Starter KitA production-grade multi-platform monorepo demonstrating shared business logic across Web and Mobile. Showcases engineering practices, decision-making and AI-assisted optimization for senior full-stack
win4r / Skill CreatorClaude Code skill for creating and optimizing Claude Code skills. Includes optimization principles for LLM attention, router pattern, classification design, and prompt engineering.
devmahmud / Advanced Javascript ProgrammingThis advanced JavaScript course is designed for experienced developers looking to deepen their understanding of JavaScript and expand their skills in web development and software engineering. The course covers advanced topics and best practices, enabling students to build complex applications and optimize existing ones.
dcarpintero / AI EngineeringAI Engineering: Annotated NBs to dive into Self-Attention, In-Context Learning, RAG, Knowledge-Graphs, Fine-Tuning, Model Optimization, and many more.
aryannzzz / Ppo Walker RlEnd-to-end reinforcement learning project training a 2D bipedal robot to walk using Proximal Policy Optimization (PPO) in PyBullet. Includes reward engineering experiments, structured hyperparameter ablations, TensorBoard analysis, and evaluation pipelines.
melon95 / PromptlyManage and generate AI prompts effortlessly. Create, organize, and optimize for LLMs with dynamic templates, version control, and analytics. Perfect for developers, boost efficiency via data-driven prompt engineering. Unlock AI potential with seamless tools.
thieung / Dev ToolboxA curated collection of specialized scripts and CLI utilities designed to optimize local development workflows, specifically tailored for AI-assisted engineering.
chestercc1997 / Re VEALReVEAL is a framework that combines Graph Neural Networks (GNNs) for architecture-level reverse engineering of optimized multipliers to assist in formal verification.
Asma-Mohsin / Model Predictive Controller Using AIMPC, or Model Predictive Control, is an advanced control strategy that uses a mathematical model and predictions of future behavior to optimize control actions over a finite time horizon. It is widely used in engineering and automation systems to improve performance, handle constraints, and adapt to changing conditions in real-time.
ardorlab / MIDASA flexible optimization framework for nuclear engineering optimization problems
