JBCA-SKA Machine Learning Club

We are a collection of researchers based at the Jodrell Bank Centre for Astrophysics (JBCA - University of Manchester) and Square Kilometer Array (SKA) head quarters at Jodrell Bank. We are interested in the application of machine learning to a wide range of scientific and engineering challenges. Our goal is to share machine learning expertise, solve interesting problems, and develop a community of active collaboration. We run a range of activities, including hacknights, lunch talks, journal club discussions and workshops. You can access these resources and find out more about us on this website and our Github page.

Journal Club

We run monthly journal club (currently via Zoom) discussing relevant papers in machine learning with applications in astronomy.

Hacknight Challenges

We run hacknights in the Lovel seminar room of the Alan Turing building with free pizza and prizes.

Machine Learning Lunches

We run a monthly seminar with introdcutory talks on different machine learning algorithms as well as talks on applications.

Machine Learning workshop

13-15th of November 2018.

In order to better understand the opportunities machine learning could offer data-intensive researchers, we are running a 3-day workshop that will provide introductory sessions on data exploration, a diverse range of speakers from academia and industry, and networking opportunities to meet with other data-intensive researchers and professionals. Our plans for subsequent workshops are currently on hold until it becomes safe to attend in-person events.

Resources

Here is a list of resources. We will add to this.

Our github repo

This repository will contain our hacknights and talks given at machine learning lunches

Coursera ML course

This is a free online course which introduces many machine learning algorithms.

scikit-learn

Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

scikit-image

scikit-image is an open source image processing library for the Python programming language.[2] It includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more. It is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Get in touch

If you have any questions please feel free to get in touch.

  • Address

    Alan Turing Building
    Manchester, M13 9PL
    UK

  • Email

    jbca.machinelearning at gmail .com