IntelPython / scikit-learn_bench
scikit-learn_bench benchmarks various implementations of machine learning algorithms across data analytics frameworks. It currently support the scikit-learn, DAAL4PY, cuML, and XGBoost frameworks for commonly used machine learning algorithms.
☆117Updated 2 weeks ago
Alternatives and similar repositories for scikit-learn_bench:
Users that are interested in scikit-learn_bench are comparing it to the libraries listed below
- Utilities for Dask and CUDA interactions☆305Updated this week
- FIL backend for the Triton Inference Server☆77Updated last week
- Data Parallel Extension for NumPy☆108Updated this week
- Python bindings for UCX☆134Updated last week
- Python SYCL bindings and SYCL-based Python Array API library☆110Updated this week
- Data Parallel Extension for Numba☆81Updated 5 months ago
- Distributed XGBoost on Ray☆148Updated 10 months ago
- oneCCL Bindings for Pytorch*☆95Updated 2 weeks ago
- RAPIDS GPU-BDB☆108Updated last year
- oneAPI Collective Communications Library (oneCCL)☆232Updated last week
- The CUDA target for Numba☆112Updated this week
- Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application☆1,277Updated this week
- An Aspiring Drop-In Replacement for Pandas at Scale☆75Updated 3 years ago
- ☆98Updated 3 weeks ago
- A benchmark to measure performance of popular Gradient boosting algorithms against popular ML datasets.☆38Updated 2 years ago
- Convert scikit-learn models and pipelines to ONNX☆581Updated this week
- oneAPI Data Analytics Library (oneDAL)☆637Updated this week
- Example Numba implementations of functions☆175Updated 2 years ago
- Productionize machine learning predictions, with ONNX or without☆65Updated last year
- A collection of Machine Learning examples to get started with deploying RAPIDS in the Cloud☆141Updated 6 months ago
- RAPIDS Memory Manager☆575Updated this week
- General policies for MLPerf™ including submission rules, coding standards, etc.☆28Updated last month
- MLPerf™ logging library☆36Updated 2 weeks ago
- Provide Python access to the NVML library for GPU diagnostics☆234Updated 5 months ago
- [ARCHIVED] Dask support for distributed GDF object --> Moved to cudf☆136Updated 5 years ago
- MLCube® is a project that reduces friction for machine learning by ensuring that models are easily portable and reproducible.☆155Updated 7 months ago
- A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python☆325Updated 7 months ago
- Experimental plugin for scikit-learn to be able to run (some estimators) on Intel GPUs via numba-dpex.☆16Updated last year
- NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale da…☆1,081Updated 8 months ago
- Universal model exchange and serialization format for decision tree forests☆767Updated this week