NVIDIA-Merlin / NVTabularLinks
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
☆1,135Updated 2 months ago
Alternatives and similar repositories for NVTabular
Users that are interested in NVTabular are comparing it to the libraries listed below
Sorting:
- NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocess…☆866Updated last year
- ☆350Updated 4 years ago
- Merlin Models is a collection of deep learning recommender system model reference implementations☆293Updated last year
- HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training☆1,039Updated 3 months ago
- Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.☆1,238Updated last month
- High performance model preprocessing library on PyTorch☆647Updated last year
- Pytorch domain library for recommendation systems☆2,449Updated this week
- Behavioral "black-box" testing for recommender systems☆469Updated 2 years ago
- A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.☆692Updated last month
- High performance distributed framework for training deep learning recommendation models based on PyTorch.☆411Updated 6 months ago
- Solutions to Recommender Systems competitions☆200Updated 3 years ago
- Train and run Pytorch models on Apache Spark.☆342Updated 2 years ago
- Universal model exchange and serialization format for decision tree forests☆800Updated 2 weeks ago
- The merlin dataloader lets you rapidly load tabular data for training deep leaning models with TensorFlow, PyTorch or JAX☆422Updated last year
- Merlin Systems provides tools for combining recommendation models with other elements of production recommender systems (like feature sto…☆94Updated last year
- For recording and retrieving metadata associated with ML developer and data scientist workflows.☆667Updated 9 months ago
- RAPIDS Sample Notebooks☆580Updated 2 years ago
- Coarse-grained lineage and tracing for machine learning pipelines.☆471Updated 3 years ago
- Factorization Machines for Recommendation and Ranking Problems with Implicit Feedback Data☆175Updated last year
- Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet f…☆1,871Updated last week
- Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO☆735Updated last month
- RAPIDS Community Notebooks☆555Updated 11 months ago
- Library for exploring and validating machine learning data☆780Updated 6 months ago
- Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.☆453Updated last week
- A JupyterLab extension for displaying dashboards of GPU usage.☆667Updated this week
- Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflow☆241Updated 2 years ago
- A collection of Machine Learning examples to get started with deploying RAPIDS in the Cloud☆144Updated last year
- Distributed XGBoost on Ray☆152Updated last year
- Fast SHAP value computation for interpreting tree-based models☆550Updated 2 years ago
- TensorFlow Recommenders is a library for building recommender system models using TensorFlow.☆1,991Updated last month