banditml / Banditml
Licence: gpl-3.0
A lightweight contextual bandit & reinforcement learning library designed to be used in production Python services.
Stars: ✭ 127
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What's banditml?
banditml is a lightweight contextual bandit & reinforcement learning library designed to be used in production Python services. This library is developed by Bandit ML and ex-authors of Facebook's applied reinforcement learning platform, Reagent.
Specifically, this repo contains:
- Feature engineering & preprocessing
- Model implementations
- Model training workflows
- Model serving code for Python services
Supported models
Models supported:
- Contextual Bandits (small datasets)
- [x] Linear bandit w/ ε-greedy exploration
- [x] Random forest bandit w/ ε-greedy exploration
- [x] Gradient boosted decision tree bandit w/ ε-greedy exploration
- Contextual Bandits (medium datasets)
- [x] Neural bandit with ε-greedy exploration
- [x] Neural bandit with UCB-based exploration (via. dropout exploration)
- [x] Neural bandit with UCB-based exploration (via. mixture density networks)
- Reinforcement Learning (large datasets)
4 feature types supported:
-
Numeric: standard floating point features
- e.g.
{totalCartValue: 39.99}
- e.g.
-
Categorical: low-cardinality discrete features
- e.g.
{currentlyViewingCategory: "men's jeans"}
- e.g.
-
ID list: high-cardinality discrete features
- e.g.
{productsInCart: ["productId022", "productId109"...]} - Handled via. learned embedding tables
- e.g.
-
"Dense" ID list: high-cardinality discrete features, manually mapped to dense feature vectors
- e.g
{productId022: [0.5, 1.3, ...], productId109: [1.9, 0.1, ...], ...}
- e.g
Docs
pip install banditml
License
GNU General Public License v3.0 or later
See COPYING to see the full text.
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