Name: Xuzheng Lu
Type: User
Company: George Washington University
Bio: M.S. Computer Science, George Washington University / M.S. Software Engineering, Wuhan University / B.Eng. Electronic Information, Southwest Jiaotong University
Location: Washington, D.C.
Xuzheng Lu's Projects
Project of AI Challenger Global Competition.
AIND Project: Planning Search on Air Cargo Problem
AIND Project - Solving Constraint Satisfaction Problems by implementing the N-Queens problem using symbolic constraints.
Project of AIND: Build an adversarial search agent to play the game "Isolation".
AIND Project - Using search agents to play around with PACMAN game.
AIND Project - Sign Language Recognition System
AIND Project - Using Simulated Annealing to solve the Traveling Salesman Problem (TSP) between US state capitals.
# Solve Sudoku with AI.
Convolutional neural networks for artistic style transfer.
Website
小白的Python入门教程实战篇:网站+iOS App源码→ http://t.cn/R2PDyWN 赞助→ http://t.cn/R5bhVpf
Background subtraction and object detection models implemented in Python.
My .bashrc config for bash.
A python implementation of Block Cipher.
My implement of Capsule and CapsNet by TensorFlow.
A simple tensorflow implementation of CapsNet (by Dr. G. Hinton), based on my understanding. This repository is built with an aim to simplify the concept, implement and understand it.
CatBoost is an open-source gradient boosting on decision trees library with categorical features support out of the box for Python, R
Project of CCF.
https://cn.udacity.com/course/deep-learning-nanodegree-foundation--nd101/
Session 10
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
Projects in my deep learning class.
Repo for the Deep Learning Nanodegree Foundations program.
Distributed Hash Table (DHT) based on Golang.
An auto-encoder to compress the MNIST dataset.
DLND project - predicting daily bike rental ridership.
DLND Project - Implementation of a DNN using TensorFlow.
A dog breed classifier based on transfer learning, using VGG, ResNet, Inception, and Xception.