CatBoost is described as 'Open-source gradient boosting on decision trees library with categorical features support out of the box for Python, R' and is an app. There are four alternatives to CatBoost for a variety of platforms, including Mac, Windows, Linux, Web-based and Python apps. The best CatBoost alternative is TensorFlow, which is both free and Open Source. Other great apps like CatBoost are Training Mule, MXNet and Deeplearning4j.
TensorFlow is an open source software library for machine learning in various kinds of perceptual and language understanding tasks.
TensorFlow is the most popular Windows, Mac & Linux alternative to CatBoost.
TensorFlow is the most popular Open Source & free alternative to CatBoost.
Training Mule allows you or your team to easily label images, providing you with the datasets that you require for the best results. With your images labelled, we will train the network of your choice and provide you with the model ready for use.
Training Mule is the most popular Web-based alternative to CatBoost.
MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both...
Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs.
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