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book1_python-for-beginners

Book_1_《编程不难》 | 鸢尾花书：从加减乘除到机器学习；请多多批评指正！

book2_beauty-of-data-visualization

Book_2_《可视之美》 | 鸢尾花书：从加减乘除到机器学习，欢迎批评指正

book3_elements-of-mathematics

Book_3_《数学要素》 | 鸢尾花书：从加减乘除到机器学习；上架；欢迎继续纠错，纠错多的同学还会有赠书！

book4_power-of-matrix

Book_4_《矩阵力量》 | 鸢尾花书：从加减乘除到机器学习；上架！

book5_essentials-of-probability-and-statistics

Book_5_《统计至简》 | 鸢尾花书：从加减乘除到机器学习；上架！

book6_first-course-in-data-science

Book_6_《数据有道》 | 鸢尾花书：从加减乘除到机器学习；欢迎大家批评指正！纠错多的同学会得到赠书感谢！

book7_visualizations-for-machine-learning

Book_7_《机器学习》 | 鸢尾花书：从加减乘除到机器学习；欢迎批评指正

chatglm-6b

ChatGLM-6B：开源双语对话语言模型 | An Open Bilingual Dialogue Language Model

chatgpt-feishu

给飞书准备的 ChatGPT 机器人

chinatextbook

人教版小学到大学数学

dash-no-license

Check out Dash, the Documentation Browser for 200+ APIs https://kapeli.com/dash

dcmh

PyTorch implementation for paper "Deep Cross-Modal Hashing"

deeplob-deep-convolutional-neural-networks-for-limit-order-books

This jupyter notebook is used to demonstrate our recent work, "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books", published in IEEE Transactions on Singal Processing. We use FI-2010 dataset and present how model architecture is constructed here. The FI-2010 is publicly avilable and interested readers can check out their paper.

dgcpn

Deep Graph-neighbor Coherence Preserving Network for Unsupervised Cross-modal Hashing

djsrh

The code for Deep Joint-Semantics Reconstructing Hashing for Large-Scale Unsupervised Cross-Modal Retrieval (ICCV 2019)

docker

Synology nas docker

ebooks

eBook分享大集合：主要以IT领域经典书籍收藏，以备不时之需。

elegantpaper

Elegant LaTeX Template for Working Papers

faceswap

Deepfakes Software For All

feishu-chatbot

:point_right: 部署飞书机器人，和ChatGPT等流行的大模型聊天

feishu-openai-stream-chatbot

🥖可以流式输出文本的飞书openai机器人

fgcrossnet_acmmm2019

Source code of our ACM MM 2019 paper "A New Benchmark and Approach for Fine-grained Cross-media Retrieval".

frm

FRM七本书配套代码

gch

Graph Convolutional Network Hashing for Cross-Modal Retrieval, IJCAI2019

lob

Benchmark Dataset of Limit Order Book in China Markets

machine-learning-notes

This is the notes of the way of machine learning study. You may find something useful in it.

match-trade

最高效的交易所撮合引擎，采用伦敦外汇交易所LMAX开源的Disruptor框架，用Hazelcast进行分布式内存存取，以及原子性操作。使用数据流的方式进行计算撮合序列，采用价格水平独立撮合逻辑，实现高效大数据撮合。

multi-horizon-forecasting-for-limit-order-books

py4fi2nd

Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.

python-machine-learning-book-3rd-edition

The "Python Machine Learning (3rd edition)" book code repository