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liquidsvm/liquidsvm 0.6.0
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
Scala versions: 2.11 -
saucam/shiva 0.1.1
A library for Simple High dimensional Indexed Vector search Algorithms
Scala versions: 3.x 2.13 -
whylabs/whylogs 0.7.0
An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈
Scala versions: 2.12 -
alibaba/alink 1.6.2
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
Scala versions: 2.11 -
h2oai/h2o-3 3.30.0.3
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Scala versions: 2.11 -
recommenders-team/recommenders 0.6.6
Best Practices on Recommendation Systems
Scala versions: 2.12 -
deepjavalibrary/djl 0.31.0
An Engine-Agnostic Deep Learning Framework in Java
Scala versions: 2.12 -
mrdimosthenis/synapses 7.3.1
A group of neural-network libraries for functional and mainstream languages
Scala versions: 2.13 -
tupol/spark-xkmeans 0.0.1
Extension to the standard K-Means implementation of Spark ML library
Scala versions: 2.11 -
mlflow/mlflow 2.18.0
Open source platform for the machine learning lifecycle
Scala versions: 2.13 2.12 -
catboost/catboost 1.2.7
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.
Scala versions: 2.13 2.12