Liangchao Wu's repositories
GoogleImagesDownloader
Enlarge training dataset by searching images with specified keywords in google and download the presented images
AmazonRobot
Amazon商品引流的 python 爬虫
ThesaurusSpider
下载搜狗、百度、QQ输入法的词库文件的 python 爬虫，可用于构建不同行业的词汇库
ThesaurusParser
搜狗、百度、QQ输入法的词库文件的 Java 解析程序，配合 ThesaurusSpider 使用
KeywordExtraction
Implementation of algorithm in keyword extraction,including TextRank,TF-IDF and the combination of both
MachineLearningAlgorithm
Implementation of some machine learning algorithms
ViterbiAlgorithm
Viterbi Algorithm for HMM
WuLC.github.io
personal website
ImageCaption
Image Captioning with Google‘s NIC For AI Challenger
MarkdownImageUploader
Simple tool for uploading image to github repository and generate url of the image
DeployMachineLearningModel
deploy machine learning model with flask, docker, jenkins and k8s
DistributedSystemInGo
code, lecture notes and papers for course http://nil.csail.mit.edu/6.824/2017/schedule.html
MachineLearningWithSpark
Python Code for the book Machine Learning With Spark
paper-reading
深度学习经典、新论文逐段精读
CodeSnippets
Some code snippets that may be useful
auto-xxqg
最新版的 自动学习强国
Books
Some special ebooks
EmotionRecognition
emotion recognition with pytorch
FacialExpressionRecognition
facial expression recognition
fedlearner
A multi-party collaborative machine learning framework
Large_Scale_Machine_Learning_With_Python
jupyter notebook for the book Large Scale Machine Learning With Python
MarkDownImages
images for markdown document, see how to use in https://github.com/WuLC/MarkdownImageUploader
Neural-Networks-and-Deep-Learning
Programming homework for the course Neural Networks and Deep Learning（https://www.coursera.org/learn/neural-networks-deep-learning/）
qlib
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.