Need advice about which tool to choose?Ask the StackShare community!
Add tool
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.
Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn MorePros of scikit-learn
Pros of XGBoost
Pros of scikit-learn
- Scientific computing23
- Easy18
Pros of XGBoost
Be the first to leave a pro
Sign up to add or upvote prosMake informed product decisions
Cons of scikit-learn
Cons of XGBoost
Cons of scikit-learn
- Limited2
Cons of XGBoost
Be the first to leave a con
Sign up to add or upvote consMake informed product decisions
What is scikit-learn?
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
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
Need advice about which tool to choose?Ask the StackShare community!
Jobs that mention scikit-learn and XGBoost as a desired skillset
What companies use scikit-learn?
What companies use XGBoost?
What companies use scikit-learn?
What companies use XGBoost?
See which teams inside your own company are using scikit-learn or XGBoost.
Sign up for StackShare EnterpriseLearn MoreSign up to get full access to all the companiesMake informed product decisions
What tools integrate with scikit-learn?
What tools integrate with XGBoost?
What tools integrate with XGBoost?
Sign up to get full access to all the tool integrationsMake informed product decisions
Blog Posts
+42 48
40265
What are some alternatives to scikit-learn and XGBoost?
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.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
H2O
H2O.ai is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark.
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
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.