A compilation of various ML and DL models and ways to optimize the their inferences.
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Updated
Nov 10, 2023 - Jupyter Notebook
A compilation of various ML and DL models and ways to optimize the their inferences.
Códigos PYTHON. Pandas, Scikit-Learning, Rapids, Cuml, Cudf.
GPU-based ML to classify Higgs boson signal from background in particle physics using RAPIDS framework
Python from an HPC viewpoint, the most practical tools, and various indispensable libraries for HPC use cases.
The Incredible RAPIDS: a curated list of tutorials, papers, projects, communities and more relating to RAPIDS.
Rapidsai_Machine_learnring_on_GPU
Awesome list of alternative dataframe libraries in Python.
Rapid large-scale fractional differencing with NVIDIA RAPIDS and GPU to minimize memory loss while making a time series stationary. 6x-400x speed up over CPU implementation.
머신러닝/딥러닝(PyTorch, TensorFlow) 전용 도커입니다. 한글 폰트, 한글 자연어처리 패키지(konlpy), 형태소 분석기, Timezone 등의 설정 등을 추가 하였습니다.
🚕 A spreadsheet-like data preparation web app that works over Optimus (Pandas, Dask, cuDF, Dask-cuDF, Spark and Vaex)
GPU accelerated cross filtering with cuDF.
🚚 Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.
PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer
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