drewafromsky Goto Github PK
Name: Drew Afromsky
Type: User
Bio: GenAI at Google and previously AWS Network Firewall and JP Morgan Chase & Co.
Name: Drew Afromsky
Type: User
Bio: GenAI at Google and previously AWS Network Firewall and JP Morgan Chase & Co.
Microservices architecture deployed via API Gateway, AWS EKS, AWS AppMesh, and Docker, Kubernetes, and Flask
Document Q&A over The Full Stack's Corpus
The Hugging Face course on Transformers
Collaborative book for CS249r: Tiny Machine Learning
Accelerating Data Augmentation with CUDA and OpenCL
Find winners in a lottery game
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Multi-Label Text Classfication of PubMed Articles
Optimized and Naive Non-Square Matrix Multiplication With CUDA and OpenCL
Notebooks using the Hugging Face libraries 🤗
Code samples for Office Add-in development on the Microsoft 365 platform.
Parallel Computing for Converting an RGB Image to Grayscale and Matrix Transpose Operation
This repository contains the latest source code of th spring-boot-microservices tutorial
2D convolution and 1D histogram calculation was performed in both CUDA and OpenCL. 2D convolution was implemented, taking advantage of both shared memory/tiles and global memory (naive methods). Tiled 2D convolution was performed in CUDA only. For naive 2D convolution, the input to the algorithm is an [M X N] matrix and a [K X K] kernel of odd dimension sizes. The output after convolution remained the same size as the input; zero padding was performed to take into account halo/ghost cells, when the kernel was ”acting” on ”non-existent” pixels/matrix elements. For the tiled 2D convolution, the kernel size was fixed: [5 x 5] to avoid dealing with dynamic memory allocation. For both methods, a serial implementation of 2D convolution was performed using scipy function (signal.convolve2D). Execution times for 2D convolution CUDA naive, 2D convolution CUDA tiled, and 2D convolution serial were recorded and plotted for comparison. Execution times for 2D convolution in OpenCL were compared to 2D convolution in serial and plotted as well. Matrices for both CUDA and OpenCL were initialized and iteratively increased in size in both dimensions by the same factor. Similarly, for 1D histogram calculation, execution times were recorded in both OpenCL and CUDA, and serial code, and then plotted and compared. One plot was created for CUDA versus serial. A second plot was created for OpenCL versus serial.
Provide a web app that simulates wind turbines emitting metrics, breaking, and repairing, in real-time
ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.