scikit-learn vs XGBoost: What are the differences?
scikit-learn: Easy-to-use and general-purpose machine learning in Python. scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license; XGBoost: Scalable and Flexible Gradient Boosting. 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.
scikit-learn and XGBoost belong to "Machine Learning Tools" category of the tech stack.
scikit-learn is an open source tool with 36.5K GitHub stars and 17.9K GitHub forks. Here's a link to scikit-learn's open source repository on GitHub.
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What is scikit-learn?
What is XGBoost?
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