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adgat

Modeling the Momentum Spillover Effect for Stock Prediction via Attribute-Driven Graph Attention Networks

berkeley-cs61b

Lecture Notes of CS61B Spring 2019.

bilingual_book_maker

Make bilingual epub books Using AI translate

complex-network

复杂网络研究资源整理和基础知识学习

corex

CorEx or "Correlation Explanation" discovers a hierarchy of informative latent factors. This reference implementation has been superseded by other versions below.

crypto-art

Data repository for paper: Quantifying NFT-driven networks in crypto art

data-science-interviews

Data science interview questions and answers

data-science-notes

数据科学的笔记以及资料搜集

datasets

A repository of pretty cool datasets that I collected for network science and machine learning research.

euler

A distributed graph deep learning framework.

eventtriplesextraction

An experiment and demo-level tool for text information extraction (event-triples extraction), which can be a route to the event chain and topic graph, 基于依存句法与语义角色标注的事件三元组抽取，可用于文本理解如文档主题链，事件线等应用。

interdisciplinary-research

Utilize Boguan thesis data to observe the evolution of interdisciplinary collaboration

learn-git-hub

test

leeml-notes

李宏毅《机器学习》笔记，在线阅读地址：https://datawhalechina.github.io/leeml-notes

ml

regression

ml-notes

notes about machine learning

mlfinlab

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

ner-bert-pytorch

PyTorch solution of named entity recognition task Using Google AI's pre-trained BERT model.

research-on-bitcoin-market-by-event-analysis

scweet

A simple and unlimited twitter scraper : scape tweets, likes, retweets, following, followers, user info, images...

skeleton-sp19

stock-knowledge-graph

利用网络上公开的数据构建一个小型的证券知识图谱/知识库

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

team-learning-data-mining

主要存储Datawhale组队学习中“数据挖掘/机器学习”方向的资料。

test

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tttt

twint

An advanced Twitter scraping & OSINT tool written in Python that doesn't use Twitter's API, allowing you to scrape a user's followers, following, Tweets and more while evading most API limitations.

visualising_stocks_correlations

youtube-tutorials