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vectorization

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VectorizedMultiAgentSimulator

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

  • Updated Jun 26, 2024
  • Python

A compute framework for turning complex data into vectors. Build multimodal vectors with ease and define weights at query time so you don't need a custom reranking algorithm to optimise results. Go straight from notebook to production with the same SDK.

  • Updated Jun 25, 2024
  • Jupyter Notebook

This project is part of my Consumer Sentiment Analysis class at Towson University, focusing on evaluating and understanding customer feedback on Spotify. By analyzing customer reviews sourced from Kaggle, we aim to extract insights into user satisfaction and areas of improvement for Spotify.

  • Updated Jun 25, 2024
  • Jupyter Notebook

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