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README.md

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* **Easy**: Regardless of whether you are a data scientist or machine learning practitioner, we've made it easy for anybody to use HugeCTR with plenty of [documents](https://nvidia-merlin.github.io/HugeCTR/main/hugectr_user_guide.html), [notebooks](https://github.com/NVIDIA-Merlin/HugeCTR/tree/main/notebooks) and [samples](https://github.com/NVIDIA-Merlin/HugeCTR/tree/main/samples).
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* **Domain Specific**: HugeCTR provides the [essentials](https://github.com/NVIDIA-Merlin/HugeCTR#core-features), so that you can efficiently deploy your recommender models with very large embedding.
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**NOTE**: If you have any questions in using HugeCTR, please file an issue or join our [Slack channel](https://join.slack.com/t/hugectr/shared_invite/zt-25vv45v7l-ioczWeHEttHaku2VJR9ZNw) to have more interactive discussions.
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**NOTE**: If you have any questions in using HugeCTR, please file an issue or join our [Slack channel](https://join.slack.com/t/hugectr/shared_invite/zt-29fptzv4w-s4bA3TkDn54YEHLKIS4Qsw) to have more interactive discussions.
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## Table of Contents
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* [Core Features](https://nvidia-merlin.github.io/HugeCTR/main/hugectr_core_features.html)

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