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@@ -602,7 +602,7 @@
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5. [TensorWatch](https://github.com/microsoft/tensorwatch) - Debugging and visualization for deep learning
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6. [ML Workspace](https://github.com/ml-tooling/ml-workspace) - All-in-one web-based IDE for machine learning and data science.
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7. [dowel](https://github.com/rlworkgroup/dowel) - A little logger for machine learning research. Log any object to the console, CSVs, TensorBoard, text log files, and more with just one call to `logger.log()`
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-8. [Neptune](https://neptune.ml/) - Lightweight tool for experiment tracking and results visualization.
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+8. [Neptune](https://neptune.ai/) - Lightweight tool for experiment tracking and results visualization.
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9. [CatalyzeX](https://chrome.google.com/webstore/detail/code-finder-for-research/aikkeehnlfpamidigaffhfmgbkdeheil) - Browser extension ([Chrome](https://chrome.google.com/webstore/detail/code-finder-for-research/aikkeehnlfpamidigaffhfmgbkdeheil) and [Firefox](https://addons.mozilla.org/en-US/firefox/addon/code-finder-catalyzex/)) that automatically finds and links to code implementations for ML papers anywhere online: Google, Twitter, Arxiv, Scholar, etc.
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10. [Determined](https://github.com/determined-ai/determined) - Deep learning training platform with integrated support for distributed training, hyperparameter tuning, smart GPU scheduling, experiment tracking, and a model registry.
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11. [DAGsHub](https://dagshub.com/) - Community platform for Open Source ML – Manage experiments, data & models and create collaborative ML projects easily.
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Chaitanya Prakash Bapat