cedrichwong Goto Github PK
Name: CedricHuang
Type: User
Bio: When I wrote this code, only God and I understood what I did. Now only God knows.
Location: Bellevue, WA
Blog: cedrichwong.github.io
Name: CedricHuang
Type: User
Bio: When I wrote this code, only God and I understood what I did. Now only God knows.
Location: Bellevue, WA
Blog: cedrichwong.github.io
My personal
Official Repository for the Manning Book Getting MEAN with MongoDB, Express, Angular and Node, 2nd Edition.
Deep learning shines brightly in computer vision, and many problems that traditional methods cannot solve are being overcome one by one. However, the high computational cost also dramatically limits the use of deep learning, and its computationally intensive characteristics are particularly prominent on platforms with limited computing resources such as mobile devices and embedded devices. High performance is the pursuit of modern deep learning training frameworks. Researchers use many operators when implementing algorithms, and many of these operators are non-computational, such as transpose, zip, conditional slice, irregular split/concatenate, and top-k. The fine-grained operator takes more and more time in the model training process. There are few operators in the classification model, and the operators in the detection and other models take up even more than 50% of the time. Therefore, the high performance of the training framework relies heavily on the overall optimization of these continuous operators. In this article, the team members will specify the compilation platform, architecture, and instruction set during the compilation process. It can make the compilation as close as possible to the characteristics of the Arm architecture. For the optimized compilation of Arm processors and their instruction sets, the experimental results will be compared with the performance indicators of the algorithms compiled from general instructions.
For the realization of a series of classic machine learning algorithms and simple models, the Python language is used, and the basic practice and visualization provided by some libraries of Numpy and Matplotlib are involved.
🌈‒ the Ethereum wallet that lives in your pocket
A Social Media Web Application Create by using React Framework, MongoDB, GraphQL
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.