|about 1 year ago||20 days ago|
|Jupyter Notebook||Jupyter Notebook|
|MIT License||MIT License|
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Simulating the limit order book
2 projects | reddit.com/r/quant | 2 Jan 2021
Not sure if helpful but I did my master's thesis about how to build a computational artificial market (in Julia which is rather an easy language to read) and published the source code: https://github.com/Miksus/thesis-computational-artificial-market
We haven't tracked posts mentioning Deep-Learning-Machine-Learning-Stock yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
tsfresh - Automatic extraction of relevant features from time series:
FinanceDataReader - Financial data reader
bulbea - :boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling
TradingGym - Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.
deltapy - DeltaPy - Tabular Data Augmentation (by @firmai)
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
pandas-profiling - Create HTML profiling reports from pandas DataFrame objects
machine-learning-for-trading - Code for Machine Learning for Algorithmic Trading, 2nd edition.
Algo-Trading - This is my github repository where I post trading strategies, tutorials and research on quantitative finance with R, C++ and Python. Some of the topics explored include: machine learning, high frequency trading, NLP, technical analysis and more. Hope you enjoy it!