Keras VS xgboost

Compare Keras vs xgboost and see what are their differences.

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, Dask, Flink and DataFlow (by dmlc)
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Keras xgboost
79 11
61,044 25,636
0.5% 0.6%
9.9 9.6
5 days ago 4 days ago
Python C++
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Keras

Posts with mentions or reviews of Keras. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-27.

xgboost

Posts with mentions or reviews of xgboost. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-05-05.

What are some alternatives?

When comparing Keras and xgboost you can also consider the following projects:

MLP Classifier - A handwritten multilayer perceptron classifer using numpy.

Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

scikit-learn - scikit-learn: machine learning in Python

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

tensorflow - An Open Source Machine Learning Framework for Everyone

mlpack - mlpack: a fast, header-only C++ machine learning library

catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]

LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.