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An end-to-end open source platform for machine learning with a comprehensive ecosystem of tools and libraries.
An end-to-end open source platform for machine learning with a comprehensive ecosystem of tools and libraries.
A library that enables PyTorch, Chainer, MXNet, and NumPy users to write TensorBoard events with simple function calls.
An interactive visual interface for exploring and debugging black-box machine learning models without writing code.
A Ruby API for TensorFlow, enabling machine learning and deep learning within Ruby applications.
A TensorBoard dashboard for visualizing and comparing Zipline algorithmic trading backtests in real-time.
A TensorBoard JupyterLab plugin that integrates TensorBoard directly into JupyterLab with improved user experience and long-term maintenance.
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