Skip to content
#

ensemble-machine-learning

Here are 213 public repositories matching this topic...

This code demonstrates the use of machine learning to model the multimodal nature of a single cell. Using machine learning to predict RNA from DNA, that is, using chromatin accessibility data to predict the RNA gene expression and to predict surface protein from RNA, that is, using RNA sequence data to predict surface protein levels in a cell

  • Updated Jun 1, 2024
  • Jupyter Notebook

This project uses an ensemble of CNN, RNN, and VGG16 models to enhance CIFAR-10 image classification accuracy and robustness. By combining multiple architectures, we significantly outperform single-model approaches, achieving superior classification performance.

  • Updated Jun 1, 2024
  • Jupyter Notebook

Improve this page

Add a description, image, and links to the ensemble-machine-learning topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the ensemble-machine-learning topic, visit your repo's landing page and select "manage topics."

Learn more