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6 materials found

Scientific topics: Toxicology  or Machine learning 


Machine Learning & BioStatistics Hackathon 2020

Materials created at the Machine Learning and BioStatistics hackathon organised by ELIXIR-GR (CERTH) in October and November 2020.

Scientific topics: Computer science, Statistics and probability, Machine learning

Keywords: machine learning, biostatistics, eLearning, EeLP

Resource type: Training materials

WEBINAR: Getting started with deep learning

This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with deep learning’. This webinar took place on 21 July 2021.

Are you wondering what deep learning is and how it might be useful in your research? This high level overview introduces...

Scientific topics: Machine learning

Keywords: Deep learning

OpenRiskNet: Ontology Walkthrough and Workshop

Workshop of 1.5h where the eNanoMapper ontology and a few uses are discussed. The exercises walk the audience trough the principles, uses, and demonstrates how they can actively work with the ontology.

Scientific topics: Ontology and terminology, Toxicology

Resource type: Tutorial

Adding nanomaterial data

This tutorial describes how nanomaterial data can be added to an eNanoMapper server using a RDF format.

Scientific topics: Database management, Toxicology

Keywords: nanotoxicology, enanomapper, resource description framework, ontology

Resource type: Tutorial

Deep Learning using a Convolutional Neural Network

This course part focuses on a recent machine learning method known as deep learning that emerged as a promising disruptive approach, allowing knowledge discovery from large datasets in an unprecedented effectiveness and efficiency. It is particularly relevant in research areas, which are not...

Scientific topics: Machine learning

Resource type: Video

Introduction to Machine Learning Algorithms

This course offers basics of analysing datasets with machine learning algorithms and data mining techniques in order to understand foundations of learning from large quantities of data.
It starts with general methods for data analysis in order to understand clustering, classification, and...

Scientific topics: Machine learning

Resource type: Video