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多平台新闻 & 内容爬虫集合 | Multi-platform News & Content Crawler Suite 支持：微信公众号、Twiiter、今日头条、网易新闻、搜狐新闻、腾讯新闻、Naver、Detik、Quora 等主流平台 Supports crawling news & content from WeChat, Toutiao, Netease, Sohu, Tence…
小红书笔记 | 评论爬虫、抖音视频 | 评论爬虫、快手视频 | 评论爬虫、B 站视频 ｜ 评论爬虫、微博帖子 ｜ 评论爬虫、百度贴吧帖子 ｜ 百度贴吧评论回复爬虫 | 知乎问答文章｜评论爬虫
Python code for bulk control of a genetically targeted cell population through a fiberoptic
LSTM Stock Predictor: Due to the volatility of cryptocurrency speculation, investors will often try to incorporate sentiment from social media and news articles to help guide their trading strategi…
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
Official electron build of draw.io
Posit Cheat Sheets - Can also be found at https://posit.co/resources/cheatsheets/.
Code files for Silva et al., Nature Neuroscience (2021)
time series forecasting using pytorch，including ANN,RNN,LSTM,GRU and TSR-RNN，experimental code
time series forecasting using keras, inlcuding LSTM,RNN,MLP,GRU,SVR and multi-lag training and forecasting method, ICONIP2017 paper.
List of papers, code and experiments using deep learning for time series forecasting
Project analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple features to predict stock prices and then s…
Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
This is the project for deep learning in stock market prediction.
Python package for analyzing behavioral data for Brain Observatory: Visual Behavior
Hierarchical, iterative clustering for analysis of transcriptomics data in R
https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1
简单粗暴 TensorFlow 2 | A Concise Handbook of TensorFlow 2 | 一本简明的 TensorFlow 2 入门指导教程
Tensorflow 2.0 Notes 提供了TF2.0案例实战以及TF2.0基础实战，目标是帮助那些希望和使用Tensorflow 2.0进行深度学习开发和研究的朋友快速入门，其中包含的Tensorflow 2.0教程基本通过测试保证可以成功运行(有问题的可以提issue，笔记网站正在建设中)。
Stock markets are an essential component of the economy. Their prediction naturally arouses afascination in the academic and financial world. Indeed, financial time series, due to their widerange a…
By combining GARCH(1,1) and LSTM model implementing predictions.
A hybrid model to predict the volatility of stock index with LSTM and GARCH-type input parameters