NVTabular
Introduction
Core Features
Accelerated Training
Examples
Additional Resources
NVTabular
»
Welcome to NVTabular’s documentation!
Welcome to NVTabular’s documentation!
Introduction
Benefits
Installation
Installing NVTabular Using Conda
Installing NVTabular with Docker
Examples and Tutorials
Feedback and Support
Core Features
TensorFlow and PyTorch Interoperability
HugeCTR Interoperability
Multi-GPU Support
Multi-Node Support
Multi-Hot Encoding and Pre-Existing Embeddings
Shuffling Datasets
Cloud Integration
Accelerated Training
TensorFlow
PyTorch
HugeCTR
Examples
Getting Started with Movielens
Download and Convert
ETL with NVTabular
Training with TensorFlow
Training with PyTorch
Advanced Ops with Outbrain
Download and Convert
ETL with NVTabular
Training with TensorFlow
Scaling to Large Datasets with Criteo
Download and Convert
ETL with NVTabular
Training with TensorFlow
Training with HugeCTR
Training with FastAI
Triton Inference with TensorFlow
Triton Inference with HugeCTR
Winning Solution of the RecSys2020 Competition
Overview
Getting Started
Preparing our dataset
Splitting dataset into training and test
Feature Engineering
Training our model
Tabular Data with Rossmann
Download and Convert
ETL with NVTabular
Training with TensorFlow
Training with PyTorch
Training with FastAI
Multi-GPU Example
NVTabular + Dask Integration
Simple Multi-GPU Toy Example
Notes on Shuffling
Additional Resources
API Documentation
Workflow
Dataset
Operators
ColumnGroup
Torch Dataloader
Torch Layers
TensorFlow Dataloader
TensorFlow Layers
Architecture
Operations
A Higher Level of Abstraction
Cloud Integration
Amazon Web Services
Google Cloud Platform
Troubleshooting
Checking the Schema of the Parquet File
Setting the Row Group Size for the Parquet Files
Github Repo
Indices and tables
Index
Module Index
Search Page
Other Versions
v: v0.5.2
Tags
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Branches
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