bestrookever Goto Github PK
Name: BestRookEver
Type: User
Location: Shanghai, China
BestRookEver's Projects
2018-iflytek-marketing-algorithms-competition-finals-rank1
2018科大讯飞营销算法大赛（冠军方案）
awesome-gradient-boosting-papers
A curated list of gradient boosting research papers with implementations.
boruta_py
Python implementations of the Boruta all-relevant feature selection method.
clickhouse-net
Yandex ClickHouse fully managed .NET client
cplusplus-_implementation_of_introduction_to_algorithms
《算法导论》第三版中算法的C++实现
cpptrader
High performance components for building Trading Platform such as ultra fast matching engine, order book processor
ctp
已经不再维护，请移步到XAPI2项目
deep-ctr-prediction
CTR prediction models based on deep learning(基于深度学习的广告CTR预估模型)
deep-recommender-system
深度学习在推荐系统中的应用及论文小结。
efficient-pytorch
My best practice of training large dataset using PyTorch.
financial-machine-learning
A curated list of practical financial machine learning (FinML) tools and applications in Python.
lightgbm
A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.
ltsf-linear
[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"
openquantbook
OpenQuant系统的入门手册
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
quantbox.apiprovider
OpenQuant2014的XAPI插件
quantbox.data
二进制行情存储格式
quantbox.datareceiver
行情接收器
quantbox.datasimulator
直接读取QuantBox.Data数据进行回测的工具
quantbox_xapi
正在升级XAPI2，请关注新版，老版不再维护
spacetimeformer
Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal Forecasting."
terminal
The new Windows Terminal, and the original Windows console host -- all in the same place!
tianshou
An elegant PyTorch deep reinforcement learning library.
time-series-library
A Library for Advanced Deep Time Series Models.
transfer-learning-time-series
Transfer 🤗 Learning for Time Series Forecasting
xapi2
统一行情交易接口第2版
xapi3
原XAPI2，清理了部分内容，仓库更简洁
xlearn
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
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