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Machine Learning & Reinforcement Learning

ML and RL built on the math underneath, not just the API.

Classical ML (regression, classification, clustering, anomaly detection), deep learning for vision and NLP, single-agent RL (DQN, PPO, policy gradients), and Multi-Agent RL for coordination problems. Quantization for mobile. Mentored academic foundation in MDPs, Bellman equations, and optimization theory.

PyTorchscikit-learnStable-Baselines3RLlibJAXONNX
When it fits

Right call when…

  • Your problem has structure deep learning won't solve alone.
  • You need multi-agent coordination, not just a single predictor.
  • Quantizing a research model to ship on a phone is part of the brief.
Frequently asked

Questions people ask about Machine Learning & Reinforcement Learning

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ML feasibility check?