From cf2add2840927a102a4150637136ba01d73cec32 Mon Sep 17 00:00:00 2001 From: Benedikt Schifferer Date: Tue, 4 Jul 2023 12:57:28 +0000 Subject: [PATCH] update intro --- README.md | 2 +- docs/source/imgs/merlin_benefits.png | Bin 0 -> 61721 bytes docs/source/imgs/merlin_deployment.png | Bin 0 -> 444079 bytes docs/source/imgs/merlin_logo.png | Bin 0 -> 14713 bytes docs/source/imgs/merlin_training.png | Bin 0 -> 138570 bytes docs/source/imgs/merlin_usecases.png | Bin 0 -> 138056 bytes docs/source/intro.rst | 61 +++++++++++++++++++++++++ docs/source/toc.yaml | 2 +- 8 files changed, 63 insertions(+), 2 deletions(-) create mode 100644 docs/source/imgs/merlin_benefits.png create mode 100644 docs/source/imgs/merlin_deployment.png create mode 100644 docs/source/imgs/merlin_logo.png create mode 100644 docs/source/imgs/merlin_training.png create mode 100644 docs/source/imgs/merlin_usecases.png create mode 100644 docs/source/intro.rst diff --git a/README.md b/README.md index 93957a42f..2d2bcc246 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ ![GitHub tag (latest SemVer)](https://img.shields.io/github/v/tag/NVIDIA-Merlin/Merlin?sort=semver) ![GitHub License](https://img.shields.io/github/license/NVIDIA-Merlin/Merlin) -[![Documentation](https://img.shields.io/badge/documentation-blue.svg)](https://nvidia-merlin.github.io/Merlin/stable/README.html) +[![Documentation](https://img.shields.io/badge/documentation-blue.svg)](https://nvidia-merlin.github.io/Merlin/stable/intro.html) NVIDIA Merlin is an open source library that accelerates recommender systems on NVIDIA GPUs. 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zg37XK$%EH9jkSAtJ4iMY-g)74gVo0Uj*VTkhmSw!*8CGc;Wt(1Dqkn`wL0Qhn`7Si z>Q?Cnw+g4~6yYGH!li8aode*V1YBT!Cv`>sf*Z?DWNiCd)PZK_=PI0}EXcVzrLTT=DwGk%T}*KEMEoT8p&4!ZV9zH5 z(x$L@^uq4y54UP%4=18wkl&0KtiAt~HXfl1`O!vB*r`p?d>CP>`_ is a library for feature engineering and preprocessing the dataset. It provides implementation of common techniques (e.g. Normalization) and more advanced ones. It scales to a dataset larger than (GPU) memory by streaming the dataset in chunks. + +Training +------------- + +NVIDIA Merlin has multiple options to train a recommender model to provide flexibility to the user and address the complex and diverse techniques in the community. + +`Merlin Models `_ provides high-quality implementations for classical machine learning models and deep learning based models using **TensorFlow** as a backend. It provides implementations for **ranking, retrieval and session-based models (GRU or transformer-based)** with a standardized API. + +`Transformers4Rec `_ is a library for **session-based recommendation with deep learning models (Transformers, RNNs)** using **PyTorch** as a backend. It provides implementations for transformer-based architectures. + +Native **TensorFlow** or **PyTorch** can be used to define and train deep learning based models. + +Deploying Recommender Systems +===================== + +.. image:: ./imgs/merlin_deployment.png + :align: center + +Recommender models are often one component in a pipeline with multiple stages. Generating recommendations often requires multiple steps. For example, out-of-stock items should be removed from the recommendations. + +`Merlin Systems `_ is a tool to build pipelines for generating recommendations. Its API enables users to define complex multi-stage pipelines, by combining single components (e.g. trained model) or connecting to additional services (e.g. feature store, ANN). Merlin systems can produce recommendations offline as batch jobs or deploy the pipeline to Triton Inference Server for online predictions. + +NVIDIA Triton Inference Server is an open source solution to scale, run and deploy machine learning and AI models from any framework on any GPU- or CPU-based infrastructure. It is used by many companies in production. diff --git a/docs/source/toc.yaml b/docs/source/toc.yaml index 3140d57c0..63ba7f1d8 100644 --- a/docs/source/toc.yaml +++ b/docs/source/toc.yaml @@ -2,7 +2,7 @@ root: index subtrees: - caption: Contents entries: - - file: README.md + - file: intro title: Introduction - file: guide/recommender_system_guide.rst title: Recommender System Guide