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Type: User
Type: User
18.06 course at MIT
❤️ 21-Points Health is an app you can use to monitor your health.
An Invitation to 3D Vision: A Tutorial for Everyone
[CVPR2020] Adversarial Latent Autoencoders
Real-Time and Accurate Multi-Person Pose Estimation&Tracking System
超级速查表 - 编程语言、框架和开发工具的速查表,单个文件包含一切你需要知道的东西 :zap:
:page_facing_up: Awesome CV is LaTeX template for your outstanding job application
A curated list of temporal action localization/detection and related area (e.g. temporal action proposal) resources.
微信小程序开发资源汇总 :100:
📜 Brief Intro to LaTeX for beginners that helps you use LaTeX with ease. Comments and Contributions are welcomed :thumbsup:
TensorFlow code and pre-trained models for BERT
Personal blog, managed by Makefile
"我的阅历"
The most popular HTML, CSS, and JavaScript framework for developing responsive, mobile first projects on the web.
C--compiler which implements LL(1)\LR(0)\SLR\LR(1) and semantic analysis and MIPS generate
Implementation of the Capsule-Forensics-v2
The official GitHub mirror of the Chromium source
CS 15-213: Introduction to Computer Systems in 2017 Spring, CMU
计算机图形学-学习笔记
吴恩达老师的机器学习课程个人笔记
:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++
Public facing notes page
Introduction to machine learning and data mining How can a machine learn from experience, to become better at a given task? How can we automatically extract knowledge or make sense of massive quantities of data? These are the fundamental questions of machine learning. Machine learning and data mining algorithms use techniques from statistics, optimization, and computer science to create automated systems which can sift through large volumes of data at high speed to make predictions or decisions without human intervention. Machine learning as a field is now incredibly pervasive, with applications from the web (search, advertisements, and suggestions) to national security, from analyzing biochemical interactions to traffic and emissions to astrophysics. Perhaps most famously, the $1M Netflix prize stirred up interest in learning algorithms in professionals, students, and hobbyists alike. This class will familiarize you with a broad cross-section of models and algorithms for machine learning, and prepare you for research or industry application of machine learning techniques. Background We will assume basic familiarity with the concepts of probability and linear algebra. Some programming will be required; we will primarily use Matlab, but no prior experience with Matlab will be assumed. (Most or all code should be Octave compatible, so you may use Octave if you prefer.) Textbook and Reading There is no required textbook for the class. However, useful books on the subject for supplementary reading include Murphy's "Machine Learning: A Probabilistic Perspective", Duda, Hart & Stork, "Pattern Classification", and Hastie, Tibshirani, and Friedman, "The Elements of Statistical Learning".
:mortar_board: My solutions to Harvard University's CS50 Introduction to Computer Science (2017, 2018) #CS50 #GD50 #WEB50
《动手学深度学习》:面向中文读者、能运行、可讨论。英文版即伯克利“深度学习导论(STAT 157)”教材。
Yolo v4 (v3/v2) - Windows and Linux version of Darknet Neural Networks for object detection (Tensor Cores are used)
深度学习和NLP随笔
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.