rnyak Goto Github PK

course-v3

The 3rd edition of course.fast.ai

cudf

cuDF - GPU DataFrame Library

cugraph

cuGraph - RAPIDS Graph Analytics Library

cuml

cuML - RAPIDS Machine Learning Library

cusignal

cuSignal

cuspatial

CUDA-accelerated GIS and spatiotemporal algorithms

customer_churn

cuxfilter

GPU accelerated cross filtering with cuDF. Docs here:

examples

fastai_roberta

collection of work pertinent to integrating Roberta with fastai:

finetune

Scikit-learn style model finetuning for NLP

jupyter-intro-xfel-jan17

Introduction to Jupyter Notebook

labs

Container Orchestration Labs

markdown_readme

Markdown - you can mark up titles, lists, tables, etc., in a much cleaner, readable and accurate way if you do it with HTML.

notebooks-contrib

RAPIDS Community Notebooks

nvtabular

A library that sits on top of RAPIDS cuDF library providing a range of benefits for processing extremely large tabular datasets, particularly those that do not fit in GPU or CPU memory. NVTabular has many capabilities including fast terabyte-scale data preparation and accelerated tabular data loading, all on GPU, which streamline the first step for both training and inference to any deep recommender system pipelines.

publications

server

The Triton Inference Server provides an optimized cloud and edge inferencing solution.

sigir-ecom-data-challenge

spotify_mpd_two_tower

Building two tower models with Spotify data in GCP

systems

t4r

text_classification

training

this includes the files from the introduction to git course

transformers

🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.

transformers4rec

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.