Curated list of machine learning and deep learning frameworks and resources for JVM
KotlinDL: a high-level Deep Learning API written in Kotlin and inspired by Keras, backed by TensorFlow Java API. KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras models for inference, and leveraging transfer learning for tweaking existing pre-trained models to your tasks.
deeplearning4j: Deep Learning framework in Java that supports the whole cycle: from data loading and preprocessing to building and tuning a variety deep learning networks.
TensorFlow Java API: Java bindings for TensorFlow.
DJL: Open-source, high-level, engine-agnostic Java framework for deep learning. DJL is designed to be easy to get started with and simple to use for Java developers.
dagli: Framework for defining machine learning models, including feature generation and transformations, as directed acyclic graphs (DAGs). - linkedin/dagli
Tribuo: A machine learning library in Java that provides multi-class classification, regression, clustering, anomaly detection and multi-label classification.
Apache Spark MLlib: ML algorithms, feature preprocessing and pipelines. Scalable through distributed computations. opennlp.apache.org: The toolkit for common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, coreference resolution, language detection and more.
Apache Manout: Distributed linear algebra framework and mathematically expressive Scala DSL designed to let mathematicians, statisticians, and data scientists quickly implement their own algorithms.
SMILE: Statistical Machine Intelligence and Learning Engine (in Scala): classification, regression, clustering, association rule mining, feature selection, manifold learning, multidimensional scaling, genetic algorithms, missing value imputation, nearest neighbor search.
Apache Ignite: A set of simple, scalable and efficient tools that allow the building of predictive Machine Learning models without costly data transfers.
Kotlin∇: Kotlin∇ is a type-safe automatic differentiation framework in Kotlin. It allows users to express differentiable programs with higher-dimensional data structures and operators.
Facebook AI automatic differentiation system for the Kotlin language (not yet released).