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What is XGBoost?

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
XGBoost is a tool in the Machine Learning Tools category of a tech stack.

Who uses XGBoost?

Companies
7 companies reportedly use XGBoost in their tech stacks, including Quezx.com, Bagelcode, and DLabs.

Developers

XGBoost Integrations

Python, Java, C++, Scala, and Julia are some of the popular tools that integrate with XGBoost. Here's a list of all 5 tools that integrate with XGBoost.

Why developers like XGBoost?

Here’s a list of reasons why companies and developers use XGBoost
Top Reasons
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XGBoost's Features

  • Flexible
  • Portable
  • Multiple Languages
  • Battle-tested

XGBoost Alternatives & Comparisons

What are some alternatives to XGBoost?
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
ML Kit
ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.
See all alternatives

XGBoost's Followers
2 developers follow XGBoost to keep up with related blogs and decisions.
Sajjad vafaie
Chaoyu Yang