Exploring Machine Learning in Research, Nov 11, 2024
Description
The integration of machine learning, a subset of artificial intelligence, into various research domains has emerged as a powerful tool with vast potential. It shows promise in handling extensive datasets and integrating them into analyses, leading to more comprehensive results. Moreover, machine learning can automate processes, enhancing experimental setups and driving innovation. Advanced predictive algorithms and Gaussian methods further enable the development of precise models that can forecast outcomes with remarkable accuracy.
However, the introduction of this powerful tool calls for a careful evaluation of its application across different research fields. Ethical and legal considerations must be addressed, as the inherent biases within social trends can be learned and perpetuated if results are not meticulously evaluated and interpreted.
Additionally, machine learning encompasses a variety of approaches, not just neural networks. Understanding the limitations and requirements of the available tools is essential to maximise their effectiveness.
This talk will introduce a first-use handbook on different machine learning algorithms, designed to help prospective users from any field—whether business, arts, sciences, or any other discipline—familiarise themselves with the available options, their respective needs, and potential outcomes. By equipping researchers with the necessary information, the handbook will enable them to make informed decisions about whether to proceed with machine learning and how to leverage it effectively for both initial approaches and more complex, interdisciplinary collaborations across diverse fields of study.
Who can participate?
Please note that some of the content may be Aalto University specific. Note also that national legal frameworks and ethical guidelines of Finland may be used to frame the discussion. Anyone interested in the topic can join. No prior knowledge is required. The webinar is free and open to all.
Format
The session consists of a presentation and a Q&A.
Schedule and location
The training will be held online via Zoom on November 11, at 1–2.30 PM Eastern European Time (EET).
Instructor(s)
Enriqueta Noriega Benitez, Data Agent and Doctoral Researcher, Department of Bioproducts and Biosystems, School of Chemical Engineering, Aalto University, [email protected]
Aalto RDM & Open Science Training | YouTube | Privacy Notice