Repository Index

Scalable and user friendly neural :brain: forecasting algorithms.

• deep-learning
• forecasting
• esrnn
• nbeats

An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.

• deep-learning
• model-compression
• mobile-app
• automl

✨ Build a machine learning model from a prompt

• agentic-ai
• agents
• machine-learning
• ml

TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning

• ml
• automl
• transformations
• estimators

AI on the way. An auto deep learning pipe dream. An RDBMS approach to deep learning. Declarative, explainable, scalable, optimizable, easy to deploy, all that good stuff.

• pytorch
• lazy-evaluation
• python
• compiler

OpenMMLab Model Compression Toolbox and Benchmark.

• nas
• pruning
• knowledge-distillation
• spos

Machine Learning in R

• machine-learning
• data-science
• tuning
• cran

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

• bayesian-optimization
• bayesian-optimisation
• hyperparameter-optimization
• hyperparameter-tuning

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.

• svm
• regression
• classification
• machine-learning