Sherry Yu's repositories
awesome-shell
A curated list of awesome command-line frameworks, toolkits, guides and gizmos. Inspired by awesome-php.
eat_tensorflow2_in_30_days
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋
reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
git-manual
🌈 Git常用命令参考手册
COVID-19
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
GDL_code
The official code repository for examples in the O'Reilly book 'Generative Deep Learning'
Machine-Learning-with-Python
Python code for common Machine Learning Algorithms
Cpp-0-1-Resource
C++ 匠心之作 从0到1入门资料
spark-syntax
This is a repo documenting the best practices in PySpark.
ML_CIA
公众号: 机器学习荐货情报局 所有代码
CASI_Python
Python code for Computer Age Statistical Inference
advanced_policy_gradient_methods
Implementation of a few advanced policy gradient methods using tensorflow
parallel_hashing_codes
Implementation for Parallel hashing
Conference-Acceptance-Rate
Statistics of acceptance rate for the main AI conference
machine-learning-with-pyspark
Source Code for 'Machine Learning with PySpark' by Pramod Singh
handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
RLQuant
Applying Reinforcement Learning in Quantitative Trading
awesome-public-datasets
A topic-centric list of high-quality open datasets in public domains. Propose NEW data ☛☛☛PR☛☛☛
dynamic-prices
Dynamic pricing for selling perishable goods
CS537-IntroToOS-MLFQ-Scheduler
Changed the vanilla scheduler of xv6 kernel to Multi-level feedback queue(MLFQ) scheduler.
Small-Chinese-Corpus
中文语料小数据：Some useful Chinese corpus datasets
hashing-baseline-for-image-retrieval
:octocat:Various hashing methods for image retrieval and serves as the baselines
TensorFlow-and-DeepLearning-Tutorial
TensorFlow & Deep Learning Tutorial
weibo_analysis
python爬虫自动爬取指定用户的原创微博和图片，并对微博进行归类分析，最后以html图表的形式展示。
The-Art-Of-Programming-By-July
此为《编程之法：面试和算法心得》一书2014年6月老版本的原型，最新完整纸质版于2015年9月上市！