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XGBoost vs AutoGluon: What are the differences?
What is 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.
What is AutoGluon? *AutoML Toolkit for Deep Learning *. It automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy deep learning models on image, text, and tabular data.
XGBoost and AutoGluon are primarily classified as "Python Build" and "Machine Learning" tools respectively.
Some of the features offered by XGBoost are:
- Flexible
- Portable
- Multiple Languages
On the other hand, AutoGluon provides the following key features:
- Quickly prototype deep learning solutions for your data with few lines of code
- Leverage automatic hyperparameter tuning, model selection / architecture search, and data processing
- Automatically utilize state-of-the-art deep learning techniques without expert knowledge
AutoGluon is an open source tool with 1.72K GitHub stars and 193 GitHub forks. Here's a link to AutoGluon's open source repository on GitHub.
