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@@ -192,11 +192,14 @@ Note: the one marked as `Live Trading` has reasonable live trading support for a
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- [Pandas](https://github.com/pandas-dev/pandas)  | `Python`, `Cython` | - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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- [Polars](https://github.com/pola-rs/polars) | `Rust`, `Python` | - Polars is a blazingly fast DataFrames library implemented in Rust using Apache Arrow Columnar Format as memory model.
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- [Scipy](https://github.com/scipy/scipy) | `Python`, `C` | - Fundamental algorithms for scientific computing in Python
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- [Sikit-learn](https://github.com/scikit-learn/scikit-learn) | `Python`, `Cython` | - Machine learning in Python
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- [Keras](https://github.com/keras-team/keras) | `Python` | - The most user friendly Deep Learning for humans in Python
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- [TensorFlow](https://github.com/tensorflow/tensorflow) | `Python`, `C++` | - More low level Deep Learning framework
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- [Pytorch](https://github.com/pytorch/pytorch) | `Python` | - Tensors and Dynamic neural networks in Python with strong GPU acceleration
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- [PyMC](https://github.com/pymc-devs/pymc) | `Python` | - Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara
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- Machine Learning
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- [Sikit-learn](https://github.com/scikit-learn/scikit-learn) | `Python`, `Cython` | - Machine learning in Python
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- [Keras](https://github.com/keras-team/keras) | `Python` | - The most user friendly Deep Learning for humans in Python
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- [TensorFlow](https://github.com/tensorflow/tensorflow) | `Python`, `C++` | - More low level Deep Learning framework
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- [Pytorch](https://github.com/pytorch/pytorch) | `Python` | - Tensors and Dynamic neural networks in Python with strong GPU acceleration
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- [Hugging Face](https://github.com/huggingface/) - The AI community building the future.
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- [LangChain](https://github.com/langchain-ai/langchain) - Building applications with LLMs through composability
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### Computation
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