jing233 Goto Github PK
Name: Jing
Type: User
Name: Jing
Type: User
A small clone of 1024 (https://play.google.com/store/apps/details?id=com.veewo.a1024)
Up to date list of the most interesting papers in AI
Selection of resources to learn Artificial Intelligence / Machine Learning / Statistical Inference / Deep Learning / Reinforcement Learning
Solutions to AIMA (Artificial Intelligence: A Modern Approach)
互联网公司技术架构,微信/淘宝/微博/腾讯/阿里/美团点评/百度/Google/Facebook/Amazon/eBay的架构,欢迎PR补充
:book: A curated list of resources dedicated to Natural Language Processing (NLP)
计算机经典书籍📚,保留书单
Reinforcement learning resources curated
An Algorithmic Trading Library for Crypto-Assets in Python
A complete computer science study plan to become a software engineer.
Main Repository for Coding Ground
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".
Repo for the Deep Learning Nanodegree Foundations program.
Deep Learning Reading List of some of the materials i found on the web for Deep Learning beginners.
Deep Learning Tutorial notes and code. See the wiki for more info.
The original code from the DeepMind article + my tweaks
Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning
Everything you need to kick ass on your coding interview
This is a leetcode repository
lab and project code from math 156 Machine Learning
Udacity's Self-Driving Car Nanodegree project files and notes.
Learn how to design large scale systems. Prep for the system design interview.
:green_book: THE Book on Full-Stack Web Application Development covering User Experience (UX) Design/Tests, HTML5, Responsive + Functional CSS, Functional JavaScript, Mobile/Offline/Security First, Progressive Enhancement, Node.js, Hapi.js, Redux, React (Native), Elm, Elixir+Phoenix, Continuous Integration/Deployment, Testing (UX/TDD/BDD), Performance-Driven-Development and much more!
solutions to Artificial Intelligence for Robotics course on Udacity
project solutions to Udacity's Machine Learning Nanodegree
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.