Using the polyadic QML Library we trained a qmodel for the ternary classification of the Iris flower dataset on IBM quantum computers. We got the accuracy level of classical ML.
Medium post: News in Quantum Machine Learning
Watch the 15-min video presentation describing the experiment
A Python library to define, train and deploy quantum machine learning models
The original ideas behind this library are described in a research paper: Polyadic Quantum Classifier — arXiv:2007.14044
A fast quantum computer simulator optimized for Quantum Machine Learning. It uses SIMD, multicore and GPU to parallize and speedup computations
ManyQ is the underlying quantum computer simulator of PolyadicQML
A early quantum machine learning algorithm (2019)