qlib VS bulbea

Compare qlib vs bulbea and see what are their differences.

qlib

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL. (by microsoft)
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qlib bulbea
53 97
14,161 1,969
1.0% -
6.6 0.0
7 days ago over 3 years ago
Python Python
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

qlib

Posts with mentions or reviews of qlib. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-02-28.

bulbea

Posts with mentions or reviews of bulbea. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing qlib and bulbea you can also consider the following projects:

zipline - Zipline, a Pythonic Algorithmic Trading Library

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.

awesome-quant - A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

stock-prediction-deep-neural-learning - Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting

quant-trading - Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, Shooting Star, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD

best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

PyPortfolioOpt - Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

Deep_Learning_Machine_Learning_Stock - Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.

pyEX - Python interface to IEX and IEX cloud APIs

n4m-sentiment - Sentiment Analysis for your MaxMSP patches - made easy.

dwx-zeromq-connector - Wrapper library for algorithmic trading in Python 3, providing DMA/STP access to Darwinex liquidity via a ZeroMQ-enabled MetaTrader Bridge EA.

tuneta - Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models