A curated and opinionated list of resources for Chief Technology Officers, with the emphasis on startups
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Updated
Mar 24, 2024
A curated and opinionated list of resources for Chief Technology Officers, with the emphasis on startups
📖 Heuristics for effective management
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
[ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models
Democracia en Red is focusing on specific implementations of DemocracyOS. We are working now working with governments and activists all over Latin America. If you are interested in our online participation tools you can check them out on our site.
Artificial Intelligence framework for games based on libGDX or not. Features: Steering Behaviors, Formation Motion, Pathfinding, Behavior Trees and Finite State Machines
Low-code tool for automating actions on real time data | Stream processing for the users.
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.
Code and data for "Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs"
Personal notes about scientific and research works on "Decision-Making for Autonomous Driving"
Sports betting assistant (with interface) which optimizes earnings regarding odds and offers
Reinforcement Learning and Decision Making tutorials explained at an intuitive level and with Jupyter Notebooks
SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks
[NeurIPS 2022] 🛒WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents
Maze Applied Reinforcement Learning Framework
High-performance metaheuristics for optimization coded purely in Julia.
Marble - the real time decision engine for fraud and AML
A curated and opinionated list of resources for startup founders and leaders of high-growth companies
Hierarchical Bayesian modeling of RLDM tasks, using R & Python
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