IEyal's Stars
IbcAlpha/IBC
Automation of Interactive Brokers TWS. You can download the latest release here: https://github.com/ibcalpha/ibc/releases/latest
psemdel/py-trading-bot
Trading-bot in python using django, vertorbt lib and interactive-brokers
ranaroussi/qtpylib
QTPyLib, Pythonic Algorithmic Trading
markclow/flutter_book_examples
AI4Finance-Foundation/FinRL-Meta
FinRLÂ-Meta: Dynamic datasets and market environments for FinRL.
mementum/backtrader
Python Backtesting library for trading strategies
PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original
Machine Learning for Algorithmic Trading, Second Edition - published by Packt
hackingthemarkets/backtrader-interactive-brokers
integrate backtrader with interactive brokers
PanPip/research
Contains all the Jupyter Notebooks used in our research
stjordanis/research-1
Contains all the Jupyter Notebooks used in our research
giuse88/duka
duka - Dukascopy historical data downloader
cuemacro/findatapy
Python library to download market data via Bloomberg, Eikon, Quandl, Yahoo etc.
mpatacchiola/deepgaze
Computer Vision library for human-computer interaction. It implements Head Pose and Gaze Direction Estimation Using Convolutional Neural Networks, Skin Detection through Backprojection, Motion Detection and Tracking, Saliency Map.
grananqvist/Awesome-Quant-Machine-Learning-Trading
Quant/Algorithm trading resources with an emphasis on Machine Learning
borisbanushev/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.
jjakimoto/finance_ml
Advances in Financial Machine Learning
mfrdixon/ML_Finance_Codes
Machine Learning in Finance: From Theory to Practice Book
yeemachine/kalidokit
Blendshape and kinematics calculator for Mediapipe/Tensorflow.js Face, Eyes, Pose, and Finger tracking models.
nicknochnack/Body-Language-Decoder
nicknochnack/MultiPoseMovenetLightning
A walkthrough demonstrating multi person tracking using movenet lighting
HaydenFaulkner/Tennis
A Tennis dataset and models for event detection & commentary generation
doda/advances-in-financial-ml-notes
boyboi86/AFML
All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.
PaddlePaddle/PaddleVideo
Awesome video understanding toolkits based on PaddlePaddle. It supports video data annotation tools, lightweight RGB and skeleton based action recognition model, practical applications for video tagging and sport action detection.
josephchenhk/qtrader
A Light Event-Driven Algorithmic Trading Engine
Luciferbobo/DAE-AQA
Auto-Encoding Score Distribution Regression for Action Quality Assessment
fire717/movenet.pytorch
A Pytorch implementation of MoveNet from Google. Include training code and pre-trained model.
ambianic/fall-detection
Python ML library for people fall detection
avakanski/A-Deep-Learning-Framework-for-Assessing-Physical-Rehabilitation-Exercises
A framework for quality assessment of exercises in physical rehabilitation based on skeletal joint displacements collected with a motion capture system.
kr1210/Human-Pose-Compare
Contains code on comparing actions performed by human beings and scoring them