Recent Trend

Hazel
Hazel Engine
PayloadsAllTheThings
A list of useful payloads and bypass for Web Application Security and Pentest/CTF
send
Simple, private file sharing from the makers of Firefox
windows
V2ray , Trojan, Trojan-go, NaiveProxy, shadowsocksR install tools for windows V2ray,Trojan,Trojan-go, NaiveProxy, shadowsocksR的一键安装工具windows下用(一键科学上网)
silero-models
Silero Models: pre-trained STT models and benchmarks made embarrassingly simple
vue-next
Repo for Vue 3.0 (currently in RC)
FreeCAD
This is the official source code of FreeCAD, a free and opensource multiplatform 3D parametric modeler. Issues are managed on our own bug tracker at https://www.freecadweb.org/tracker
kb
A minimalist knowledge base manager
Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
mimikatz
A little tool to play with Windows security
vagas-junior-estagio
Empresas que constantemente oferecem vagas para junior e estagiários
material-shell
A modern desktop interface for Linux. Improve your user experience and get rid of the anarchy of traditional desktop workflows. Designed to simplify navigation and reduce the need to manipulate window
dayjs
⏰ Day.js 2KB immutable date library alternative to Moment.js with the same modern API
ML_course
EPFL Machine Learning Course, Fall 2019
create-react-app
Set up a modern web app by running one command.
Background-Matting
Background Matting: The World is Your Green Screen
Kingfisher
A lightweight, pure-Swift library for downloading and caching images from the web.
istio
Connect, secure, control, and observe services.
linux-command
Linux命令大全搜索工具,内容包含Linux命令手册、详解、学习、搜集。https://git.io/linux
generative_inpainting
DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral
yearn-protocol
Yearn solidity smart contracts
pebble
RocksDB/LevelDB inspired key-value database in Go
jazzit
Laughs at your expense
moment
Parse, validate, manipulate, and display dates in javascript.
n8n
Free and open fair-code licensed node based Workflow Automation Tool. Easily automate tasks across different services.
Hero
Elegant transition library for iOS & tvOS
DAIN
Depth-Aware Video Frame Interpolation (CVPR 2019)
eat_tensorflow2_in_30_days
Tensorflow2.0 ?? is delicious, just eat it! ??
tmpmail
✉️ A temporary email right from your terminal
team-comtress-2
Team Fortress 2, but with a lot of fixes, QoL improvements and performance optimizations!
CVE-2020-1472
PoC for Zerologon - all research credits go to Tom Tervoort of Secura
DefinitelyTyped
The repository for high quality TypeScript type definitions.
rails
Ruby on Rails
stats-illustrations
R & stats illustrations by @allison_horst
pytorch-gans
My implementation of various GAN (generative adversarial networks) architectures like vanilla GAN, cGAN, DCGAN, etc.
data-science-interviews
Data science interview questions and answers
sds1

jupyter-text2code
A proof-of-concept jupyter extension which converts english queries into relevant python code
Notebooks
Learn Python for free using open-source notebooks in Hebrew.
jellyfin
The Free Software Media System
BIGTREETECH-SKR-mini-E3
BIGTREETECH SKR-mini-E3 motherboard is a ultra-quiet, low-power, high-quality 3D printing machine control board. It is launched by the 3D printing team of Shenzhen BIGTREE technology co., LTD. This bo
XiaomiADBFastbootTools
A simple tool for managing Xiaomi devices on desktop using ADB and Fastboot
fastmac
Get a MacOS or Linux shell, for free, in around 2 minutes
pipedream
Serverless integration and compute platform. Free for developers.
DeepVision
在我很多项目中用到的CV算法推理框架应用。
dive
A tool for exploring each layer in a docker image
libra
Libra’s mission is to enable a simple global payment system and financial infrastructure that empowers billions of people.
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters,
kinto

CVE-2020-1472
Test tool for CVE-2020-1472
leetcode_company_wise_questions
This is a repository containing the list of company wise questions available on leetcode premium
makani
Makani was a project to develop a commercial-scale airborne wind turbine, culminating in a flight test of the Makani M600 off the coast of Norway. All Makani software has now been open-sourced. This r
Fantasy-Premier-League
Creates a .csv file of all players in the English Player League with their respective team and total fantasy points
996.ICU
Repo for counting stars and contributing. Press F to pay respect to glorious developers.
graal
GraalVM: Run Programs Faster Anywhere ?
understand-nodejs
通过源码分析nodejs原理
tensorboard
TensorFlow's Visualization Toolkit
DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
Relativty
An open source VR headset with SteamVR supports for $200
guide-rpc-framework
A custom RPC framework implemented by Netty+Kyro+Zookeeper.(一款基于 Netty+Kyro+Zookeeper 实现的自定义 RPC 框架-附详细实现过程和相关教程。)
UTM
Virtual machines for iOS
v2ray-heroku
用于在 Heroku 上部署 V2Ray Websocket,本项目不宜做为长期使用之对策。
learning
Becoming 1% better at data science everyday
wirehole

minecraft-react

mem-doc
This is a document to help with .NET memory analysis and diagnostics.
HarmonyOS
A curated list of awesome things related to HarmonyOS. 华为鸿蒙操作系统。
radar-covid-backend-dp3t-server
DP^3T Radar COVID fork
eiten
Statistical and Algorithmic Investing Strategies for Everyone
radar-covid-backend-verification-server
Radar COVID Verification Service
radar-covid-ios
Native iOS app using DP^3T iOS sdk to handle Exposure Notification framework from Apple
radar-covid-android
Native Android app using DP^3T Android sdk to handle Exposure Notifications API from Google
react-challenge-amazon-clone

solana
Web-Scale Blockchain for fast, secure, scalable, decentralized apps and marketplaces.
cockroach
CockroachDB - the open source, cloud-native distributed SQL database.
machine-learning-for-trading
Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.
hwp.js
Open source hwp viewer and parser library powered by web technology
awesome-react
A collection of awesome things regarding React ecosystem
connectedhomeip
Project Connected Home over IP is a new Working Group within the Zigbee Alliance. This Working Group plans to develop and promote the adoption of a new connectivity standard to increase compatibility
Yolo-Fastest
⚡ Yolo universal target detection model combined with EfficientNet-lite, the calculation amount is only 230Mflops(0.23Bflops), and the model size is 1.3MB
laravel
A PHP framework for web artisans
onnxruntime
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
cim
?cim(cross IM) 适用于开发者的分布式即时通讯系统
ESP32-WiFi-Hash-Monster
WiFi Hash Purple Monster, store EAPOL & PMKID packets in an SD CARD using a M5STACK / ESP32 device
react-portfolio

Algorithms
A collection of algorithms and data structures
frp
A fast reverse proxy to help you expose a local server behind a NAT or firewall to the internet.
funNLP
中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌词库、汽车零件词库、连续英文切割、各种中文词向量、公司名字大全、古诗词库、IT词库、财经词库、成语词库、地名词库、历史名
GRAT2
We developed GRAT2 Command & Control (C2) project for learning purpose.
DescomplicandoKubernetes

aes-finder
Utility to find AES keys in running processes
mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
ultimate-python
Ultimate Python study guide for newcomers and professionals alike. ? ? ?
sushiswap-frontend

pytorch-lightning
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
awesome-flutter
An awesome list that curates the best Flutter libraries, tools, tutorials, articles and more.
Interview_Question_for_Beginner
? ? Technical-Interview guidelines written for those who started studying programming. I wish you all the best. ?
free

talk
A group video call for the web. No signups. No downloads.
bitcoin
Bitcoin Core integration/staging tree
eleventy-high-performance-blog
A high performance blog template for the 11ty static site generator.
awesome-project-ideas
Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
ghcide
A library for building Haskell IDE tooling
moon
? The minimal & fast library for functional user interfaces
jdk
JDK main-line development
Tasmota
Alternative firmware for ESP8266 with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full docum
Server
PanDownload的个人维护版本
a32nx
The A32NX Project is a community driven open source project to create a free Airbus A320neo in Microsoft Flight Simulator that is as close to reality as possible. It aims to enhance the default A320ne
keras
Deep Learning for humans
Red-Teaming-Toolkit
A collection of open source and commercial tools that aid in red team operations.
data-engineer-roadmap
Roadmap to becoming a data engineer in 2020
hivemind
Decentralized deep learning framework in pytorch. Built to train models on thousands of volunteers across the world.
scipio
Scipio is a thread-per-core framework that aims to make the task of writing highly parallel asynchronous application in a thread-per-core architecture easier for rustaceans
hoppscotch
? A free, fast and beautiful API request builder used by 75k+ developers. https://hoppscotch.io
Wav2Lip
This repository contains the codes of "A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild", published at ACM Multimedia 2020.
KingOfBugBountyTips

autoscraper
A Smart, Automatic, Fast and Lightweight Web Scraper for Python
100-nlp-papers
100 Must-Read NLP Papers
croc
Easily and securely send things from one computer to another ? ?
spark-nlp
State of the Art Natural Language Processing
display-switch
Turn a $30 USB switch into a full-featured multi-monitor KVM switch
surpriver
Find big moving stocks before they move using machine learning and anomaly detection
flink-learning
flink learning blog. http://www.flink-learning.com 含 Flink 入门、概念、原理、实战、性能调优、源码解析等内容。涉及 Flink Connector、Metrics、Library、DataStream API、Table API & SQL 等内容的学习案例,还有 Flink 落地应用的大型项目案例(PVUV、日志存储、百亿数据实时去重、监
deeplearning-models
A collection of various deep learning architectures, models, and tips
fes.js
Fes.js 是一个管理台应用解决方案,提供初始项目、开发调试、编译打包的命令行工具,内置布局、权限、数据字典、状态管理、Api等多个模块,文件目录结构即路由,用户只需要编写页面内容。基于Vue.js,内置管理台常用能力,让用户写的更少,更简单。经过多个项目中打磨,趋于稳定。
stitches
The modern styling library. Near-zero runtime, server-side rendering, multi-variant support, and best-in-class developer experience.
18S191
Course 18.S191 at MIT, fall 2020 - Introduction to computational thinking with Julia
grafana
The tool for beautiful monitoring and metric analytics & dashboards for Graphite, InfluxDB & Prometheus & More
fortify

jetstream

scikit-learn-tips
?⚡ Daily scikit-learn tips
12306
12306智能刷票,订票
desafio-6-2020

30-seconds-of-code
Short JavaScript code snippets for all your development needs
gdal
GDAL is an open source X/MIT licensed translator library for raster and vector geospatial data formats.
toBeTopJavaer
To Be Top Javaer - Java工程师成神之路
companies-sponsoring-visas
A list of companies that sponsor employees from other countries.
howtheytest
A collection of public resources about how software companies test their software
bicep

htop
htop - an interactive process viewer
portainer
Making Docker management easy.
gorm
The fantastic ORM library for Golang, aims to be developer friendly
SuperPower
Here you should find the best power supplies for your low-power projects
CompEcon2020
Computational Economics Course 2020 by Kenneth Judd
vimac
Vimium for macOS.
Windows10Debloater
Script to remove Windows 10 bloatware.
HowToHunt
Some Tutorials and Things to Do while Hunting That Vulnerability.
Hack-Tools
The all-in-one Red Team extension for Web Pentester ?
KingOfBugBountyTips

Showkase
? Showkase is an annotation-processor based Android library that helps you organize, discover, search and visualize Jetpack Compose UI elements
webrtc-for-the-curious
WebRTC for the Curious: Go beyond the APIs
matplotplusplus
Matplot++: A C++ Graphics Library for Data Visualization ??
Flutter-Course-Resources
Learn to Code While Building Apps - The Complete Flutter Development Bootcamp
flutter-development-roadmap
Flutter App Developer Roadmap - A complete roadmap to learn Flutter App Development. I tried to learn flutter using this roadmap. If you want to add something please contribute to the project. Happy L
objax

sushiswap
? SushiSwap smart contracts
Cloudreve
?支持多家云存储的云盘系统 (A project helps you build your own cloud in minutes)
learn-python
? Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.
Python-programming-exercises
100+ Python challenging programming exercises
learn-python3
Jupyter notebooks for teaching/learning Python 3
vscode-debug-visualizer
An extension for VS Code that visualizes data during debugging.
rapier
2D and 3D physics engines focused on performances.
project-guidelines
A set of best practices for JavaScript projects
d3
Bring data to life with SVG, Canvas and HTML. ???
OpenBot
OpenBot leverages smartphones as brains for low-cost robots. We have designed a small electric vehicle that costs about $50 and serves as a robot body. Our software stack for Android smartphones suppo
speakeasy
Windows kernel and user mode emulation.
Learn-Vim
A book for learning the Vim editor
maratona-fullcycle-4

arwes
Futuristic Sci-Fi and Cyberpunk Graphical User Interface Framework for Web Apps
gitignore
A collection of useful .gitignore templates
black
The uncompromising Python code formatter
airflow
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
shift-ctrl-f
? Search the information available on a webpage using natural language instead of an exact string match.
traefik
The Cloud Native Edge Router
TecoGAN
This repo will contain source code and materials for the TecoGAN project, i.e. code for a TEmporally COherent GAN
present
A terminal-based presentation tool with colors and effects.
gitpod
Gitpod is an open-source Kubernetes application providing prebuilt, collaborative development environments in your browser - powered by VS Code.
compose-samples

react-native-navigation
A complete native navigation solution for React Native
kubernetes-examples
Minimal self-contained examples of standard Kubernetes features and patterns in YAML
vscode
Visual Studio Code
cpp-httplib
A C++ header-only HTTP/HTTPS server and client library
AWS-SAA-C02-Course
Personal notes for SAA-C02 test from: https://learn.cantrill.io
clean-architecture-swiftui
A demo project showcasing the production setup of the SwiftUI app with Clean Architecture
Gooey
Turn (almost) any Python command line program into a full GUI application with one line
baiduwp-php
PanDownload网页复刻版
latexify_py
Generates LaTeX math description from Python functions.
open-source-cs-python

RAFT

volt-bootstrap-5-dashboard
⚡️ Volt Bootstrap 5 Admin Dashboard Template with vanilla Javascript
itlwm
Intel Wi-Fi Drivers
packer
Packer is a tool for creating identical machine images for multiple platforms from a single source configuration.
open-source-cs
Video discussing this curriculum:
nsfw-filter
A Google Chrome / Firefox extension that blocks NSFW images from the web pages that you load using TensorFlow JS.
sudoku-solver
Smart solution to solve sudoku in VR
desafio-4-2020

msfs-a320neo

mit-15-003-data-science-tools
Study guides for MIT's 15.003 Data Science Tools
CascadeTabNet
This repository contains the code and implementation details of the CascadeTabNet paper "CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents"
certified-kubernetes-administrator-course
Certified Kubernetes Administrator - CKA Course
everyones-guide-for-starting-up-on-wechat-network
微信互联网平民创业
manim
Animation engine for explanatory math videos
CS-Notes
我的自学笔记,在学习shell和MLSys,整理C++、算法、操作系统,后续学习分布式系统,终身更新。
egua
? Linguagem de programação simples e moderna em português
talent-plan
open source training courses about distributed database and distributed systemes
godot
Godot Engine – Multi-platform 2D and 3D game engine
desafio-3-2020

optuna
A hyperparameter optimization framework
Ventoy
A new bootable USB solution.
Alt-F4
Alternative Factorio Friday Fan Facts, also known as Alt-F4
awesome-made-by-brazilians
?? A collection of amazing open source projects built by brazilian developers
zig
General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
cxx
Safe interop between Rust and C++
lireddit

chakra-ui
⚡️ Simple, Modular & Accessible UI Components for your React Applications
VancedManager
Vanced Installer
react-native-video
A
NYPD-Misconduct-Complaint-Database
This database is a record of NYPD misconduct complaints made by the public to the Civilian Complaint Review Board (CCRB).
awesome-django
A curated list of awesome things related to Django
Front-End-Checklist
? The perfect Front-End Checklist for modern websites and meticulous developers
fet.sh
a fetch written in posix shell without any external commands (linux only)
baiduwp
PanDownload Web, built with CloudFlare Workers
machine-learning-interview
Minimum Viable Study Plan for Machine Learning Interviews from FAAG, Snapchat, LinkedIn.
RSSHub
? Everything is RSSible
metamask-extension
? ? The MetaMask browser extension enables browsing Ethereum blockchain enabled websites
amplify-flutter
Amplify Framework provides a declarative and easy-to-use interface across different categories of cloud operations.
ent
An entity framework for Go
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
element3
(WIP)fork from ElemeFE/element ,A Vue.js 3.0 UI Toolkit for Web
posthog
? PostHog is developer-friendly, open-source product analytics.
awesome-hpp
A curated list of awesome header-only C++ libraries
fabric
Hyperledger Fabric is an enterprise-grade permissioned distributed ledger framework for developing solutions and applications. Its modular and versatile design satisfies a broad range of industry use
insight
Repository for Project Insight: NLP as a Service
omatsuri
Browser application with 9 open source frontend focused tools
InfoSpider
INFO-SPIDER 是一个集众多数据源于一身的爬虫工具箱?,旨在安全快捷的帮助用户拿回自己的数据,工具代码开源,流程透明。支持数据源包括GitHub、QQ邮箱、网易邮箱、阿里邮箱、新浪邮箱、Hotmail邮箱、Outlook邮箱、京东、淘宝、支付宝、中国移动、中国联通、中国电信、知乎、哔哩哔哩、网易云音乐、QQ好友、QQ群、生成朋友圈相册、浏览器浏览历史、12306、博客园、CSDN博客、开源
element-plus
A Vue.js 3.0 UI Toolkit for Web
autoscaler
Autoscaling components for Kubernetes
magento2
All Submissions you make to Magento Inc. ("Magento") through GitHub are subject to the following terms and conditions: (1) You grant Magento a perpetual, worldwide, non-exclusive, no charge, royalty f
ts-migrate
A tool to help migrate JavaScript code quickly and conveniently to TypeScript
ar-cutpaste
Cut and paste your surroundings using AR
chinese-programmer-wrong-pronunciation
中国程序员容易发音错误的单词
labs_campaigns

AdGuardHome
Network-wide ads & trackers blocking DNS server
COLA
Clean Object-oriented & Layered Architecture
Godzilla
哥斯拉
diagrams
? Diagram as Code for prototyping cloud system architectures
PaddleDetection
Object detection and instance segmentation toolkit based on PaddlePaddle.
handcalcs
Python library for converting Python calculations into rendered latex.
mern-course-bootcamp
Complete Free Coding Bootcamp 2020 MERN Stack
handwritten.js
Convert typed text to realistic handwriting!
archivy
Archivy is a self-hosted knowledge repository that allows you to safely preserve useful content that contributes to your knowledge bank.
mall-swarm
mall-swarm是一套微服务商城系统,采用了 Spring Cloud Hoxton & Alibaba、Spring Boot 2.3、Oauth2、MyBatis、Docker、Elasticsearch等核心技术,同时提供了基于Vue的管理后台方便快速搭建系统。mall-swarm在电商业务的基础集成了注册中心、配置中心、监控中心、网关等系统功能。文档齐全,附带全套Spring Clou
umami
Umami is a simple, fast, website analytics alternative to Google Analytics.
nl-covid19-notification-app-android
Android sources for the Dutch Covid19 Notification App
contenidos
Material del curso IIC2233 Programación Avanzada ?
locast2plex
A very simple script to connect locast to Plex's live tv/dvr feature.
h1st
H1st AI solves the critical “cold-start” problem of Industrial AI: encoding human expertise to augment the lack of data, while building a smooth transition toward a machine-learning future. This probl
minGPT
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Catch2
A modern, C++-native, header-only, test framework for unit-tests, TDD and BDD - using C++11, C++14, C++17 and later (or C++03 on the Catch1.x branch)
libra
Ergonomic machine learning.
annie
? Fast, simple and clean video downloader
spotMicro
Spot Micro Quadripeg Project
LeetCode-Go
✅ Solutions to LeetCode by Go, 100% test coverage, runtime beats 100% / LeetCode 题解
bootcamp-gostack-desafios
Repositório contendo todos os desafios dos módulos do Bootcamp Gostack
NoVmp
A static devirtualizer for VMProtect x64 3.x. powered by VTIL.
fullcalendar
Full-sized drag & drop event calendar
latexify_py
Generates LaTeX math description from Python functions.
vue-nodejs-youtube-clone
This is the frontend (VueJS) of the Youtube clone called VueTube.
youtube-clone-nodejs-api
VueTube is a YouTube clone built with nodejs, expressjs & mongodb. This is the RESTful API repository.
Behinder
“冰蝎”动态二进制加密网站管理客户端
low-level-design-primer

E-commerce-Complete-Flutter-UI

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.
aws-machine-learning-university-accelerated-tab

aws-machine-learning-university-accelerated-cv

mogollar
A MongoDB UI built with Electron
BespokeSynth
Software modular synth
desafio-1-2020

desafio-1-2020

kosmonaut
A web browser engine for the space age ?
aws-machine-learning-university-accelerated-nlp

fastbook
Draft of the fastai book
Hierarchical-Localization
Visual localization made easy
TypeScript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
Penetration_Testing_POC
渗透测试有关的POC、EXP、脚本、提权、小工具等,欢迎补充、完善---About penetration-testing python-script poc getshell csrf xss cms php-getshell domainmod-xss penetration-testing-poc csrf-webshell cobub-razor cve rce sql sql-poc p
God-Of-BigData
大数据面试题,大数据成神之路开启...Flink/Spark/Hadoop/Hbase/Hive...
OSCPRepo
A list of commands, scripts, resources, and more that I have gathered and attempted to consolidate for use as OSCP (and more) study material. Commands in 'Usefulcommands' Keepnote. Bookmarks and readi
drogon
Drogon: A C++14/17 based HTTP web application framework running on Linux/macOS/Unix/Windows
papercups
Open-source live customer chat
jupyter-book
Build interactive, publication-quality documents from Jupyter Notebooks
awesome-java
Collection of awesome Java project on Github(Github 上非常棒的 Java 开源项目集合).
espflix
A free video streaming service that runs on a ESP32
servo
The Servo Browser Engine
halfmoon
Front-end framework with a built-in dark mode, designed for rapidly building beautiful dashboards and product pages.
eventnative
EventNative is an open-source data collection framework
go-github
Go library for accessing the GitHub API
yam-protocol
A stablizing reserve currency protocol
mmdetection3d
OpenMMLab's next-generation platform for general 3D object detection.
sherlock
? Hunt down social media accounts by username across social networks
computervision-recipes
Best Practices, code samples, and documentation for Computer Vision.
clean-code-javascript
? Clean Code concepts adapted for JavaScript
laravel-admin
Build a full-featured administrative interface in ten minutes
OpenJailbreak
GeoSn0w's OpenJailbreak Project, an open-source iOS 11 to iOS 13 Jailbreak project & vault.
azure-quickstart-templates
Azure Quickstart Templates
nodejs.dev
A new Node.js resource built using Gatsby.js with React.js, TypeScript, Emotion, and Remark.
KOOM
KOOM is an OOM killer on mobile platform by Kwai.
bevy
A refreshingly simple data-driven game engine built in Rust
eat_pytorch_in_20_days
Pytorch?? is delicious, just eat it! ??
datasets
? 2,000,000+ Unsplash images made available for research and machine learning
malwoverview
Malwoverview is a first response tool to perform an initial and quick triage in a directory containing malware samples, specific malware sample, suspect URL and domains. Additionally, it allows to dow
streisand
Streisand sets up a new server running your choice of WireGuard, OpenConnect, OpenSSH, OpenVPN, Shadowsocks, sslh, Stunnel, or a Tor bridge. It also generates custom instructions for all of these serv
LeetCode
LeetCode刷题记录
IntelOwl
Intel Owl: analyze files, domains, IPs in multiple ways from a single API at scale
archive-program
The GitHub Archive Program & Arctic Code Vault
rancher
Complete container management platform
Noctilucent
Using TLS 1.3 to evade censors, bypass network defenses, and blend in with the noise
data-science
? Path to a free self-taught education in Data Science!
FigmaToCode
Generate responsive pages and apps on Tailwind, Flutter and SwiftUI.
twitter-clone

my-arsenal-of-aws-security-tools
List of open source tools for AWS security: defensive, offensive, auditing, DFIR, etc.
InvoiceNet
Deep neural network to extract intelligent information from invoice documents.
macOS_Big_Sur_icons_replacements
Replacement icons for popular apps in the style of macOS Big Sur
AnimeGANv2
[Open Source]. The improved version of AnimeGAN.
bluezone-app
Bluezone - Bảo vệ mình, bảo vệ cộng đồng
awesome-sysadmin
A curated list of amazingly awesome open source sysadmin resources inspired by Awesome PHP.
facebook-scripts-dom-manipulation
An open-source project includes many scripts with no Access Token needed for Facebook users by directly manipulating the DOM.
MCinaBox
MCinaBox - A Minecraft Java Edition Launcher on Android
ai-economist
Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcemen
TikTok-Shares-Botter
Adds TikTok Shares for you.
prefect
The easiest way to automate your data
tuya-convert
A collection of scripts to flash Tuya IoT devices to alternative firmwares
crush
Crush is an attempt to make a command line shell that is also a powerful modern programming language.
pyre-check
Performant type-checking for python.
polkadot
Polkadot Node Implementation
incyber

mesh
Cloud native service mesh for the rest of us.
V2rayU
V2rayU,基于v2ray核心的mac版客户端,用于科学上网,使用swift编写,支持vmess,shadowsocks,socks5等服务协议,支持订阅, 支持二维码,剪贴板导入,手动配置,二维码分享等
TLS-poison

heroicons
A set of free MIT-licensed high-quality SVG icons for UI development.
react-native
A framework for building native apps with React.
gui.cs
Console-based user interface toolkit for .NET applications.
Atlas
Atlas: End-to-End 3D Scene Reconstruction from Posed Images
aws-sdk-go
AWS SDK for the Go programming language.
charts
Curated applications for Kubernetes
pybind11
Seamless operability between C++11 and Python
mediapipe
MediaPipe is the simplest way for researchers and developers to build world-class ML solutions and applications for mobile, edge, cloud and the web.
proffy-discovery
A proposta do projeto é uma aplicação que possa ligar quem deseja aprender, com quer ensinar. É possível encontrar alunos para o que você leciona, ou encontrar o professor para aquela matéria que você
mixer
Add-on for real-time collaboration in Blender.
iOS-DeviceSupport
This repository holds the device support files for the iOS, and I will update it regularly.
simdjson
Parsing gigabytes of JSON per second
amplify-js
A declarative JavaScript library for application development using cloud services.
lottie-ios
An iOS library to natively render After Effects vector animations
Faze4-Robotic-arm
All files for 6 axis robot arm with cycloidal gearboxes .
xiaobaiyang

Javascript
A repository for All algorithms implemented in Javascript (for educational purposes only)
blog-post-workflow
Show your latest blog posts from any sources or StackOverflow activity on your GitHub profile/project readme automatically using the RSS feed
reverse-interview
Questions to ask the company during your interview
expo
An open-source platform for making universal native apps with React. Expo runs on Android, iOS, and the web.
955.WLB
955 不加班的公司名单 - 工作 955,work–life balance (工作与生活的平衡)
A-to-Z-Resources-for-Students
✅ Curated list of resources for college students
TDengine
An open-source big data platform designed and optimized for the Internet of Things (IoT).
django-jazzmin
Jazzy theme for Django
full-stack-fastapi-postgresql
Full stack, modern web application generator. Using FastAPI, PostgreSQL as database, Docker, automatic HTTPS and more.
Reflection_Summary
算法理论基础知识应知应会
Best-websites-a-programmer-should-visit
? Some useful websites for programmers.
bpytop
Linux/OSX/FreeBSD resource monitor
TelemetrySourcerer
Enumerate and disable common sources of telemetry used by AV/EDR.
instagrabber
InstaGrabber, the open-source Instagram client for Android. Originally by @AwaisKing.
pe_tree

Powershell-Scripts
Helpful list of powershell scripts I have found/created
drawio
Source to app.diagrams.net
analytics
Simple and privacy-friendly alternative to Google Analytics
pycaret
An open source, low-code machine learning library in Python
Ciphey
Automated decryption tool
Data-Science-Interview-Resources
A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.
ps4-ipv6-uaf

UNSAM_2020c2_Python
Curso de programación en Python - 2do cuatrimestre 2020 - UNSAM
gpu.js
GPU Accelerated JavaScript
how-to-secure-anything
How to systematically secure anything: a repository about security engineering
paperview
A high performance X11 animated wallpaper setter
core
? JAVClub - 让你的大姐姐不再走丢
home-cloud
The "cloud" at home
haoel.github.io

InstaPy
? Instagram Bot - Tool for automated Instagram interactions
bat
A cat(1) clone with wings.
DeOldify
A Deep Learning based project for colorizing and restoring old images (and video!)
educative.io_courses
this is downloadings of all educative.io free student subscription courses as pdf from GitHub student pack
rustlings
? Small exercises to get you used to reading and writing Rust code!
trackerslist
Updated list of public BitTorrent trackers
Statistical-Learning-Method_Code
手写实现李航《统计学习方法》书中全部算法
mobile
React Native client application for COVID Shield on iOS and Android
binary_search
A collection of improved binary search algorithms.
mirai

TapTap
Port of the double tap on back of device feature from Android 11 to any armv8 Android device
complete-javascript-course
Starter files, final projects and FAQ for my Complete JavaScript course
icons
Official open source SVG icon library for Bootstrap.
oneflow
OneFlow is a performance-centered and open-source deep learning framework.
ml-engineer-roadmap
WIP: Roadmap to becoming a machine learning engineer in 2020
hvmi
Hypervisor Memory Introspection Core Library
fhe-toolkit-linux
IBM Fully Homomorphic Encryption Toolkit For Linux
teenyicons
Tiny minimal 1px icons designed to fit in the smallest places.
project-citadel
An open source project management tool with Kanban boards
covid-alert-app
Exposure notification client application / Application client de notification d'exposition
ChromeAppHeroes
?谷粒-Chrome插件英雄榜, 为优秀的Chrome插件写一本中文说明书, 让Chrome插件英雄们造福人类~ ChromePluginHeroes, Write a Chinese manual for the excellent Chrome plugin, let the Chrome plugin heroes benefit the human~ 公众号「0加1」同步更新
SSPanel-Uim
SSPanel V3 魔改再次修改版
UnusualVolumeDetector
Gets the last 5 months of volume history for every ticker, and alerts you when a stock's volume exceeds 10 standard deviations from the mean within the last 3 days
formik
Build forms in React, without the tears ?
learn-cantrill-io-labs
Standard and Advanced Demos for learn.cantrill.io courses
TransCoder
Public release of the TransCoder research project https://arxiv.org/pdf/2006.03511.pdf
bounty-targets-data
This repo contains hourly-updated data dumps of bug bounty platform scopes (like Hackerone/Bugcrowd/Intigriti/etc) that are eligible for reports
CtCI-6th-Edition
Cracking the Coding Interview 6th Ed. Solutions
windows95
?? Windows 95 in Electron. Runs on macOS, Linux, and Windows.
SkyArk
SkyArk helps to discover, assess and secure the most privileged entities in Azure and AWS
interviews
Everything you need to know to get the job.
Android-Analysis
Getting Genymotion & Burpsuite setup for Android Mobile App Analysis
detext
DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks
awesome-java
A curated list of awesome frameworks, libraries and software for the Java programming language.
workflow

tye
Tye is a tool that makes developing, testing, and deploying microservices and distributed applications easier. Project Tye includes a local orchestrator to make developing microservices easier and the
java-design-patterns
Design patterns implemented in Java
java8-tutorial
Modern Java - A Guide to Java 8
generator-jhipster
JHipster is a development platform to quickly generate, develop, & deploy modern web applications & microservice architectures.
stayaway-app
Official repository for the STAYAWAY COVID mobile application
api-guidelines
Microsoft REST API Guidelines
win10script
This is the Ultimate Windows 10 Script from a creation from multiple debloat scripts and gists from github.
tutorials
Just Announced - "Learn Spring Security OAuth":
Otto
Otto makes machine learning an intuitive, natural language experience.? Facebook AI Challenge winner
first-order-model
This repository contains the source code for the paper First Order Motion Model for Image Animation
laravel-best-practices
Laravel best practices
hiring-without-whiteboards
⭐️ Companies that don't have a broken hiring process
PyTorch_YOLOv4
PyTorch implementation of YOLOv4
macintosh.js
A virtual Apple Macintosh with System 8, running in Electron. I'm sorry.
QuickCut
Your most handy video processing software
Super-mario-bros-PPO-pytorch
Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
arrow
Apache Arrow is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficien
swift
The Swift Programming Language
flutter
Flutter makes it easy and fast to build beautiful apps for mobile and beyond.
pikvm
Open and cheap DIY IP-KVM based on Raspberry Pi
ILSpy
.NET Decompiler with support for PDB generation, ReadyToRun, Metadata (&more) - cross-platform!
aluraflix
⚛️ Projeto feito durante a Imersão React da Alura
starship
☄?️ The minimal, blazing-fast, and infinitely customizable prompt for any shell!
leonsans
Leon Sans is a geometric sans-serif typeface made with code in 2019 by Jongmin Kim.
MCVmComputers
Order computer parts from a satellite orbiting around your minecraft world and build actual working computers with them!
CleanArchitecture.WebApi
An implementation of Clean Architecture for ASP.NET Core 3.1 WebAPI. Built with loosely coupled architecture and clean-code practices in mind.
NutShell
RISC-V SoC designed by students in UCAS
bartosz-basics-of-haskell
Code and exercises from Bartosz Milewski's Basics of Haskell Tutorial
fullstack-starterkit
GraphQL first full-stack starter kit with Node, React. Powered by TypeScript
movement-tracking
UP - DOWN - LEFT - RIGHT movement tracking.
OSCP-Exam-Report-Template-Markdown
? OSCP Exam Report Template in Markdown
react-native-instagram-clone
A React Native app - Clone Instagram mobile app (In progress)
felicette
Satellite imagery for dummies.
neovim
Vim-fork focused on extensibility and usability
machine-learning-roadmap
A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
python-cheatsheet
Comprehensive Python Cheatsheet
awesome-cold-showers
For when people get too hyped up about things
cutter
Free and Open Source Reverse Engineering Platform powered by radare2
ORB_SLAM3
ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM
RustScan
Faster Nmap Scanning with Rust
openpilot
openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for over 85 supported car makes and models.
retinaface
The remake of the https://github.com/biubug6/Pytorch_Retinaface
awesome-gpt3

GitHub520
?让你“爱”上 GitHub,解决访问时图裂、加载慢的问题。
LeetcodeTop
汇总各大互联网公司容易考察的高频leetcode题?
angular-tetris
Tetris game built with Angular 10 and Akita ?
umi-core
UMI Core Go Library
RustScan
Faster Nmap Scanning with Rust
rpi-power-monitor
Raspberry Pi Power Monitor
umi-core-py
UMI Core Python Library
gpt3-sandbox
The goal of this project is to enable users to create cool web demos using the newly released OpenAI GPT-3 API with just a few lines of Python.
easy_rust
Rust explained using easy English
rengine
reNgine is an automated reconnaissance framework meant for gathering information during penetration testing of web applications. reNgine has customizable scan engines, which can be used to scan the we
industry-machine-learning
A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)
umi-core-js
UMI Core JS Library
bloatbox
☑️? Get rid of bloatware and clean your Windows 10 Start menu
umi-core-php
UMI Core PHP Library
proposal-record-tuple
ECMAScript proposal for the Record and Tuple value types. | Stage 2: it will change!
jetbrains-agent-latest
jetbrains全家桶永久激活破解,不需要修改host。完美破解!共享给各个程序员兄弟使用。适用于2020版本。
applied-ml
Curated papers, articles & videos on data science & machine learning applied in production, with results.
lotus
Implementation of the Filecoin protocol, written in Go
cat
CAT 作为服务端项目基础组件,提供了 Java, C/C++, Node.js, Python, Go 等多语言客户端,已经在美团点评的基础架构中间件框架(MVC框架,RPC框架,数据库框架,缓存框架等,消息队列,配置系统等)深度集成,为美团点评各业务线提供系统丰富的性能指标、健康状况、实时告警等。
fawkes
Fawkes, privacy preserving tool against facial recognition systems. More info at http://sandlab.cs.uchicago.edu/fawkes
terminal
The new Windows Terminal and the original Windows console host, all in the same place!
kibana
Your window into the Elastic Stack
terraform
Terraform enables you to safely and predictably create, change, and improve infrastructure. It is an open source tool that codifies APIs into declarative configuration files that can be shared amongst
gotraining
Go Training Class Material :
JavaFamily
【Java面试+Java学习指南】 一份涵盖大部分Java程序员所需要掌握的核心知识。
storybook
? The UI component workshop. Develop, document, & test for React, Vue, Angular, Ember, Web Components, & more!
awesome-remote-job
A curated list of awesome remote jobs and resources. Inspired by https://github.com/vinta/awesome-python
vueuse
? Collection of Composition API utils for Vue 2 and 3
fe-interview
前端面试每日 3+1,以面试题来驱动学习,提倡每日学习与思考,每天进步一点!每天早上5点纯手工发布面试题(死磕自己,愉悦大家),3000+道前端面试题全面覆盖,HTML/CSS/JavaScript/Vue/React/Nodejs/TypeScript/ECMAScritpt/Webpack/Jquery/小程序/软技能……
stock
stock,股票系统。使用python进行开发。
awesome-ml-courses
Awesome free machine learning and AI courses with video lectures.
laravel-boilerplate
The Laravel Boilerplate Project - https://laravel-boilerplate.com
reactjs-interview-questions
List of top 500 ReactJS Interview Questions & Answers....Coding exercise questions are coming soon!!
lx-music-desktop
一个基于 electron 的音乐软件
number-verifier
Number Verifier is a SMS verification tool that makes it easy to get a disposable SMS number and bypass SMS number verifications on any site.
CyberProfDevelopmentCovidResources
An awesome list of FREE resources for training, conferences, speaking, labs, reading, etc that are free all the time or during COVID-19 that cybersecurity professionals with downtime can take advantag
opentelemetry-specification
Specifications for OpenTelemetry
front-end-interview-handbook
? No bullshit answers to the famous h5bp "Front-end Job Interview Questions"
hello-algorithm
?????? 本项目包括:1、我写的 30w 字图解算法题典 2、100 张编程类超清晰思维导图 3、100 篇大厂面经汇总 4、各语言编程电子书 100 本 5、小浩算法网站源代码 ( ?? 国人项目上榜不容易,右上角助力一波!干就对了,奥利给 !??)

machine-learning-for-trading

Jupyter Notebook LINK
Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

ML for Trading - 2nd Edition

This book aims to show how ML can add value to algorithmic trading strategies in a practical yet comprehensive way. It covers a broad range of ML techniques from linear regression to deep reinforcement learning and demonstrates how to build, backtest, and evaluate a trading strategy driven by model predictions.

In four parts with 23 chapters plus an appendix, it covers on over 800 pages:

This repo contains over 150 notebooks that put the concepts, algorithms, and use cases discussed in the book into action. They provide numerous examples that show

We highly recommend to review the notebooks while reading the book; they are usually in executed state and often contain additional information that the space constraints of the book did not permit to include.

What's new in the 2nd Edition?

First and foremost, this book demonstrates how you can extract signals from a diverse set of data sources and design trading strategies for different asset classes using a broad range of supervised, unsupervised, and reinforcement learning algorithms. It also provides relevant mathematical and statistical knowledge to facilitate the tuning of an algorithm or the interpretation of the results. Furthermore, it covers the financial background that will help you work with market and fundamental data, extract informative features, and manage the performance of a trading strategy.

From a practical standpoint, the 2nd edition aims to equip you with the conceptual understanding and tools to develop your own ML-based trading strategies. To this end, it frames ML as a critical element in a process rather than a standalone exercise, introducing the end-to-end ML for trading workflow from data sourcing, feature engineering, and model optimization to strategy design and backtesting.

More specifically, the ML4T workflow starts with generating ideas for a well-defined investment universe, collecting relevant data, and extracting informative features. It also involves designing, tuning, and evaluating ML models suited to the predictive task. Finally, it requires developing trading strategies to act on the models' predictive signals, as well as simulating and evaluating their performance on historical data using a backtesting engine. Once you decide to execute an algorithmic strategy in a real market, you will find yourself iterating over this workflow repeatedly to incorporate new information and a changing environment.

The second edition's emphasis on the ML4t workflow translates into a new chapter on strategy backtesting, a new appendix describing over 100 different alpha factors, and many new practical applications. We have also rewritten most of the existing content for clarity and readability.

The trading applications now use a broader range of data sources beyond daily US equity prices, including international stocks and ETFs. It also demonstrates how to use ML for an intraday strategy with minute-frequency equity data. Furthermore, it extends the coverage of alternative data sources to include SEC filings for sentiment analysis and return forecasts, as well as satellite images to classify land use.

Another innovation of the second edition is to replicate several trading applications recently published in top journals:

All applications now use the latest available (at the time of writing) software versions such as pandas 1.0 and TensorFlow 2.2. There is also a customized version of Zipline that makes it easy to include machine learning model predictions when designing a trading strategy.

Installation and Data Sources

Chapter Summary

The book has four parts that address different challenges that arise when sourcing and working with market, fundamental and alternative data sourcing, developing ML solutions to various predictive tasks in the trading context, and designing and evaluating a trading strategy that relies on predictive signals generated by an ML model.

The directory for each chapter contains a README with additional information on content, code examples and additional resources.

Part 1: From Data to Strategy Development

Part 2: Machine Learning for Trading: Fundamentals

Part 3: Natural Language Processing for Trading

Part 4: Deep & Reinforcement Learning

Part 1: From Data to Strategy Development

The first part provides a framework for developing trading strategies driven by machine learning (ML). It focuses on the data that power the ML algorithms and strategies discussed in this book, outlines how to engineer and evaluates features suitable for ML models, and how to manage and measure a portfolio's performance while executing a trading strategy.

01 Machine Learning for Trading: From Idea to Execution

This chapter explores industry trends that have led to the emergence of ML as a source of competitive advantage in the investment industry. We will also look at where ML fits into the investment process to enable algorithmic trading strategies.

More specifically, it covers the following topics:

02 Market & Fundamental Data: Sources and Techniques

This chapter shows how to work with market and fundamental data and describes critical aspects of the environment that they reflect. For example, familiarity with various order types and the trading infrastructure matter not only for the interpretation of the data but also to correctly design backtest simulations. We also illustrate how to use Python to access and manipulate trading and financial statement data.

Practical examples demonstrate how to work with trading data from NASDAQ tick data and Algoseek minute bar data with a rich set of attributes capturing the demand-supply dynamic that we will later use for an ML-based intraday strategy. We also cover various data provider APIs and how to source financial statement information from the SEC.

In particular, this chapter covers:

03 Alternative Data for Finance: Categories and Use Cases

This chapter outlines categories and use cases of alternative data, describes criteria to assess the exploding number of sources and providers, and summarizes the current market landscape.

It also demonstrates how to create alternative data sets by scraping websites, such as collecting earnings call transcripts for use with natural language processing (NLP) and sentiment analysis algorithms in the third part of the book.

More specifically, this chapter covers:

04 Financial Feature Engineering: How to research Alpha Factors

If you are already familiar with ML, you know that feature engineering is a crucial ingredient for successful predictions. It matters at least as much in the trading domain, where academic and industry researchers have investigated for decades what drives asset markets and prices, and which features help to explain or predict price movements.

This chapter outlines the key takeaways of this research as a starting point for your own quest for alpha factors. It also presents essential tools to compute and test alpha factors, highlighting how the NumPy, pandas, and TA-Lib libraries facilitate the manipulation of data and present popular smoothing techniques like the wavelets and the Kalman filter that help reduce noise in data. After reading it, you will know about:

05 Portfolio Optimization and Performance Evaluation

Alpha factors generate signals that an algorithmic strategy translates into trades, which, in turn, produce long and short positions. The returns and risk of the resulting portfolio determine whether the strategy meets the investment objectives.

There are several approaches to optimize portfolios. These include the application of machine learning (ML) to learn hierarchical relationships among assets and treat them as complements or substitutes when designing the portfolio's risk profile. This chapter covers:

Part 2: Machine Learning for Trading: Fundamentals

The second part covers the fundamental supervised and unsupervised learning algorithms and illustrates their application to trading strategies. It also introduces the Quantopian platform that allows you to leverage and combine the data and ML techniques developed in this book to implement algorithmic strategies that execute trades in live markets.

06 The Machine Learning Process

This chapter kicks off Part 2 that illustrates how you can use a range of supervised and unsupervised ML models for trading. We will explain each model's assumptions and use cases before we demonstrate relevant applications using various Python libraries.

There are several aspects that many of these models and their applications have in common. This chapter covers these common aspects so that we can focus on model-specific usage in the following chapters. It sets the stage by outlining how to formulate, train, tune, and evaluate the predictive performance of ML models as a systematic workflow. The content includes:

07 Linear Models: From Risk Factors to Return Forecasts

Linear models are standard tools for inference and prediction in regression and classification contexts. Numerous widely used asset pricing models rely on linear regression. Regularized models like Ridge and Lasso regression often yield better predictions by limiting the risk of overfitting. Typical regression applications identify risk factors that drive asset returns to manage risks or predict returns. Classification problems, on the other hand, include directional price forecasts.

Chapter 07 covers the following topics:

08 The ML4T Workflow: From Model to Strategy Backtesting

This chapter presents an end-to-end perspective on designing, simulating, and evaluating a trading strategy driven by an ML algorithm. We will demonstrate in detail how to backtest an ML-driven strategy in a historical market context using the Python libraries backtrader and Zipline. The ML4T workflow ultimately aims to gather evidence from historical data that helps decide whether to deploy a candidate strategy in a live market and put financial resources at risk. A realistic simulation of your strategy needs to faithfully represent how security markets operate and how trades execute. Also, several methodological aspects require attention to avoid biased results and false discoveries that will lead to poor investment decisions.

More specifically, after working through this chapter you will be able to:

09 Time Series Models for Volatility Forecasts and Statistical Arbitrage

This chapter focuses on models that extract signals from a time series' history to predict future values for the same time series. Time series models are in widespread use due to the time dimension inherent to trading. It presents tools to diagnose time series characteristics such as stationarity and extract features that capture potentially useful patterns. It also introduces univariate and multivariate time series models to forecast macro data and volatility patterns. Finally, it explains how cointegration identifies common trends across time series and shows how to develop a pairs trading strategy based on this crucial concept.

In particular, it covers:

10 Bayesian ML: Dynamic Sharpe Ratios and Pairs Trading

Bayesian statistics allows us to quantify uncertainty about future events and refine estimates in a principled way as new information arrives. This dynamic approach adapts well to the evolving nature of financial markets. Bayesian approaches to ML enable new insights into the uncertainty around statistical metrics, parameter estimates, and predictions. The applications range from more granular risk management to dynamic updates of predictive models that incorporate changes in the market environment.

More specifically, this chapter covers:

11 Random Forests: A Long-Short Strategy for Japanese Stocks

This chapter applies decision trees and random forests to trading. Decision trees learn rules from data that encode nonlinear input-output relationships. We show how to train a decision tree to make predictions for regression and classification problems, visualize and interpret the rules learned by the model, and tune the model's hyperparameters to optimize the bias-variance tradeoff and prevent overfitting.

The second part of the chapter introduces ensemble models that combine multiple decision trees in a randomized fashion to produce a single prediction with a lower error. It concludes with a long-short strategy for Japanese equities based on trading signals generated by a random forest model.

In short, this chapter covers:

12 Boosting your Trading Strategy

Gradient boosting is an alternative tree-based ensemble algorithm that often produces better results than random forests. The critical difference is that boosting modifies the data used to train each tree based on the cumulative errors made by the model. While random forests train many trees independently using random subsets of the data, boosting proceeds sequentially and reweights the data. This chapter shows how state-of-the-art libraries achieve impressive performance and apply boosting to both daily and high-frequency data to backtest an intraday trading strategy.

More specifically, we will cover the following topics:

13 Data-Driven Risk Factors and Asset Allocation with Unsupervised Learning

Dimensionality reduction and clustering are the main tasks for unsupervised learning:

More specifically, this chapter covers:

Part 3: Natural Language Processing for Trading

Text data are rich in content, yet unstructured in format and hence require more preprocessing so that a machine learning algorithm can extract the potential signal. The critical challenge consists of converting text into a numerical format for use by an algorithm, while simultaneously expressing the semantics or meaning of the content.

The next three chapters cover several techniques that capture language nuances readily understandable to humans so that machine learning algorithms can also interpret them.

14 Text Data for Trading: Sentiment Analysis

Text data is very rich in content but highly unstructured so that it requires more preprocessing to enable an ML algorithm to extract relevant information. A key challenge consists of converting text into a numerical format without losing its meaning. This chapter shows how to represent documents as vectors of token counts by creating a document-term matrix that, in turn, serves as input for text classification and sentiment analysis. It also introduces the Naive Bayes algorithm and compares its performance to linear and tree-based models.

In particular, in this chapter covers:

15 Topic Modeling: Summarizing Financial News

This chapter uses unsupervised learning to model latent topics and extract hidden themes from documents. These themes can generate detailed insights into a large corpus of financial reports. Topic models automate the creation of sophisticated, interpretable text features that, in turn, can help extract trading signals from extensive collections of texts. They speed up document review, enable the clustering of similar documents, and produce annotations useful for predictive modeling. Applications include identifying critical themes in company disclosures, earnings call transcripts or contracts, and annotation based on sentiment analysis or using returns of related assets.

More specifically, it covers:

16 Word embeddings for Earnings Calls and SEC Filings

This chapter uses neural networks to learn a vector representation of individual semantic units like a word or a paragraph. These vectors are dense with a few hundred real-valued entries, compared to the higher-dimensional sparse vectors of the bag-of-words model. As a result, these vectors embed or locate each semantic unit in a continuous vector space.

Embeddings result from training a model to relate tokens to their context with the benefit that similar usage implies a similar vector. As a result, they encode semantic aspects like relationships among words through their relative location. They are powerful features that we will use with deep learning models in the following chapters.

More specifically, in this chapter, we will cover:

Part 4: Deep & Reinforcement Learning

Part four explains and demonstrates how to leverage deep learning for algorithmic trading. The powerful capabilities of deep learning algorithms to identify patterns in unstructured data make it particularly suitable for alternative data like images and text.

The sample applications show, for exapmle, how to combine text and price data to predict earnings surprises from SEC filings, generate synthetic time series to expand the amount of training data, and train a trading agent using deep reinforcement learning. Several of these applications replicate research recently published in top journals.

17 Deep Learning for Trading

This chapter presents feedforward neural networks (NN) and demonstrates how to efficiently train large models using backpropagation while managing the risks of overfitting. It also shows how to use TensorFlow 2.0 and PyTorch and how to optimize a NN architecture to generate trading signals. In the following chapters, we will build on this foundation to apply various architectures to different investment applications with a focus on alternative data. These include recurrent NN tailored to sequential data like time series or natural language and convolutional NN, particularly well suited to image data. We will also cover deep unsupervised learning, such as how to create synthetic data using Generative Adversarial Networks (GAN). Moreover, we will discuss reinforcement learning to train agents that interactively learn from their environment.

In particular, this chapter will cover

18 CNN for Financial Time Series and Satellite Images

CNN architectures continue to evolve. This chapter describes building blocks common to successful applications, demonstrates how transfer learning can speed up learning, and how to use CNNs for object detection. CNNs can generate trading signals from images or time-series data. Satellite data can anticipate commodity trends via aerial images of agricultural areas, mines, or transport networks. Camera footage can help predict consumer activity; we show how to build a CNN that classifies economic activity in satellite images. CNNs can also deliver high-quality time-series classification results by exploiting their structural similarity with images, and we design a strategy based on time-series data formatted like images.

More specifically, this chapter covers:

19 RNN for Multivariate Time Series and Sentiment Analysis

Recurrent neural networks (RNNs) compute each output as a function of the previous output and new data, effectively creating a model with memory that shares parameters across a deeper computational graph. Prominent architectures include Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) that address the challenges of learning long-range dependencies. RNNs are designed to map one or more input sequences to one or more output sequences and are particularly well suited to natural language. They can also be applied to univariate and multivariate time series to predict market or fundamental data. This chapter covers how RNN can model alternative text data using the word embeddings that we covered in Chapter 16 to classify the sentiment expressed in documents.

More specifically, this chapter addresses:

20 Autoencoders for Conditional Risk Factors and Asset Pricing

This chapter shows how to leverage unsupervised deep learning for trading. We also discuss autoencoders, namely, a neural network trained to reproduce the input while learning a new representation encoded by the parameters of a hidden layer. Autoencoders have long been used for nonlinear dimensionality reduction, leveraging the NN architectures we covered in the last three chapters. We replicate a recent AQR paper that shows how autoencoders can underpin a trading strategy. We will use a deep neural network that relies on an autoencoder to extract risk factors and predict equity returns, conditioned on a range of equity attributes.

More specifically, in this chapter you will learn about:

21 Generative Adversarial Nets for Synthetic Time Series Data

This chapter introduces generative adversarial networks (GAN). GANs train a generator and a discriminator network in a competitive setting so that the generator learns to produce samples that the discriminator cannot distinguish from a given class of training data. The goal is to yield a generative model capable of producing synthetic samples representative of this class. While most popular with image data, GANs have also been used to generate synthetic time-series data in the medical domain. Subsequent experiments with financial data explored whether GANs can produce alternative price trajectories useful for ML training or strategy backtests. We replicate the 2019 NeurIPS Time-Series GAN paper to illustrate the approach and demonstrate the results.

More specifically, in this chapter you will learn about:

22 Deep Reinforcement Learning: Building a Trading Agent

Reinforcement Learning (RL) models goal-directed learning by an agent that interacts with a stochastic environment. RL optimizes the agent's decisions concerning a long-term objective by learning the value of states and actions from a reward signal. The ultimate goal is to derive a policy that encodes behavioral rules and maps states to actions. This chapter shows how to formulate and solve an RL problem. It covers model-based and model-free methods, introduces the OpenAI Gym environment, and combines deep learning with RL to train an agent that navigates a complex environment. Finally, we'll show you how to adapt RL to algorithmic trading by modeling an agent that interacts with the financial market while trying to optimize an objective function.

More specifically,this chapter will cover:

23 Conclusions and Next Steps

In this concluding chapter, we will briefly summarize the essential tools, applications, and lessons learned throughout the book to avoid losing sight of the big picture after so much detail. We will then identify areas that we did not cover but would be worth focusing on as you expand on the many machine learning techniques we introduced and become productive in their daily use.

In sum, in this chapter, we will

24 Appendix - Alpha Factor Library

Throughout this book, we emphasized how the smart design of features, including appropriate preprocessing and denoising, typically leads to an effective strategy. This appendix synthesizes some of the lessons learned on feature engineering and provides additional information on this vital topic.

To this end, we focus on the broad range of indicators implemented by TA-Lib (see Chapter 4) and WorldQuant's 101 Formulaic Alphas paper (Kakushadze 2016), which presents real-life quantitative trading factors used in production with an average holding period of 0.6-6.4 days.

This chapter covers: