FinRL®: Financial Reinforcement Learning. 🔥
- deep-reinforcement-learning
- drl-trading-agents
- stock-trading
- drl-algorithms
Repository Index
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Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
- inpainting
- inpainting-methods
- inpainting-algorithm
- computer-vision
Algorithms for outlier, adversarial and drift detection
- anomaly
- outlier
- concept-drift
- detection
Use evolutionary algorithms instead of gridsearch in scikit-learn
Environment for reinforcement-learning algorithmic trading models
A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
- feature-selection
- data-science
- python
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.