Repository Index

Symbolic Learning in Python and Julia

• symbolic-regression
• machine-learning
• python
• julia

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

• automl
• machine-learning
• mljar
• data-science

Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

• deep-learning
• machine-learning
• ml-platform
• ml-infrastructure

a delightful machine learning tool that allows you to train, test, and use models without writing code

• machine-learning
• machinelearning
• machine-learning-algorithms
• machine-learning-library

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

• hyperopt
• keras
• hyperparameter-optimization

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

Hyperparameter Experiments with TensorFlow and Keras

• deep-learning
• keras
• keras-tensorflow
• hyperparameter-optimization

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