hcho3

hcho3's Stars

• CodingCat/XGBoostExperiments

  repo containing XGBoost-based ML project for various purposes

  Language:Scala7

• parrt/dtreeviz

  A python library for decision tree visualization and model interpretation.

  Language:Jupyter Notebook3k337

• rui314/9cc

  A Small C Compiler

  Language:C1.9k154

• hcho3/xgboost-json-schema

  Language:Python32

• mongodb/mongo-c-driver

  The Official MongoDB driver for C language

  Language:C825457

• trivialfis/nihs-jl

  Language:C++2

• uploadcare/pillow-simd

  The friendly PIL fork

  Language:Python2.2k88

• NVIDIA/nccl

  Optimized primitives for collective multi-GPU communication

  Language:C++3.5k860

• h2oai/datatable

  A Python package for manipulating 2-dimensional tabular data structures

  Language:C++1.8k160

• orling/Poppy

  Poppy is a stack tracing and performance measurement library for C++

  Language:C++6013

• bombela/backward-cpp

  A beautiful stack trace pretty printer for C++

  Language:C++3.9k492

• dessant/lock-threads

  GitHub Action that locks closed issues, pull requests and discussions after a period of inactivity

  Language:JavaScript31736

• abandonware-pjz37/r-cmake

  R with CMake build tool

  Language:Python423

• NVIDIA/nvidia-docker

  Build and run Docker containers leveraging NVIDIA GPUs

  17.3k2k

• curl/curl

  A command line tool and library for transferring data with URL syntax, supporting DICT, FILE, FTP, FTPS, GOPHER, GOPHERS, HTTP, HTTPS, IMAP, IMAPS, LDAP, LDAPS, MQTT, POP3, POP3S, RTMP, RTMPS, RTSP, SCP, SFTP, SMB, SMBS, SMTP, SMTPS, TELNET, TFTP, WS and WSS. libcurl offers a myriad of powerful features

  Language:C36.8k6.6k

• hcho3/xgboost-fast-hist-perf-lab

  Deeper look into performance of tree_method='hist' for multi-core CPUs

  Language:C++52

• libarchive/libarchive

  Multi-format archive and compression library

  Language:C3.1k781

• pybind/pybind11

  Seamless operability between C++11 and Python

  Language:C++16.2k2.1k

• aws/amazon-sagemaker-examples

  Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

  Language:Jupyter Notebook10.3k6.8k

• Laurae2/sparsity

  R package for loading/saving sparse matrices (dgCMatrix) to SVMlight (LibFM, xgboost, LightGBM, H2O, etc.)

  Language:R53

• boostorg/random

  Boost.org random module

  Language:C++3571

• NVIDIA/nccl-tests

  NCCL Tests

  Language:Cuda991260

• CodingCat/xgboost4j-spark-scalability

  a benchmark to test scalability of xgboost4j-spark and relevant projects

  Language:Scala229

• zhengruifeng/SparkGBM

  Spark-based GBM

  Language:Terra5621

• fmtlib/fmt

  A modern formatting library

  Language:C++21.3k2.6k

• Laurae2/gbt_benchmarks

  Gradient Boosted Trees Mega Benchmark

  Language:HTML5

• uxlfoundation/oneDAL

  oneAPI Data Analytics Library (oneDAL)

  Language:C++625219

• open-mpi/ompi

  Open MPI main development repository

  Language:C2.3k884

• rufuspollock/s3-bucket-listing

  Create nice directory listings for s3 buckets with javascript and HTML.

  Language:JavaScript700302

• criteo-forks/xgboost-jars

  JARs for XGBoost built on Linux, OS X and Windows

  Language:Python5218