dabrze

ligand-classification

Project examing sparse deep learning architectures for ligand classification.

Actually-Robust-Training

Actually Robust Training - Tool Inspired by Andrej Karpathy "Recipe for training neural networks". It allows you to decompose your Deep Learning pipeline into modular and insightful "Steps". Additionally it has many features for testing and debugging neural nets.

drug-screening

💊 A project examining data from High Throughput Screening center in Poznan.

DALEX

moDel Agnostic Language for Exploration and eXplanation

nextflow-k8s-operator

Kubernetes operator for Nextflow

topography-scratch

evotorch

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.

pysubgroup

confidence-planner

A Python library for estimating confidence intervals around accuracy and sample sizes for classification experiments.

dbfe

DBFE is a Python library with feature extraction methods that facilitate classifier learning from distributions of genomic variants.

scikit-survival

Survival analysis built on top of scikit-learn

explainerdashboard

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

Pre_Surv_COVID_19

A machine learning-based model for survival prediction in COVID patients

refleX

refleX - A system for automatic anomaly detection in X-ray diffraction images.

imbalanced-learn

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

moa

MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.