https://github.com/callaghanmt-training/swd8_intro_ml

SWD8: Introduction to Machine Learning

https://github.com/callaghanmt-training/swd8_intro_ml

Repository

SWD8: Introduction to Machine Learning

https://github.com/callaghanmt-training/swd8_intro_ml/blob/main/

# SWD8: Introduction to Machine Learning

[![DOI](https://zenodo.org/badge/483669317.svg)](https://zenodo.org/badge/latestdoi/483669317)

Booking for this course is through the IT Training Unit.  

Click [here](...) to book.  

## Content

Machine learning and deep learning are very large, growing, and rapidly changing fields. They are a range of methods that learn associations from data. These can be useful for a range of problems. This course is a simple introduction to them. It aims to provide high-level, practical guidance to get started. This can help you build intuitions and make good practices a habit.

## Objectives

At the end of this workshop, learners will:

1. [ ] Understand the fundamentals of machine learning and deep learning.
2. [ ] Know how to use key tools, including:
    - [ ] [scikit-learn](https://scikit-learn.org/stable/)
    - [ ] [TensorFlow](https://www.tensorflow.org/) and [Keras](https://keras.io/)
    - [ ] [PyTorch](https://pytorch.org/) and [PyTorch Lightning](https://www.pytorchlightning.ai/)
3. [ ] Be aware of good practices for data, such as pipelines and modules.
4. [ ] Be aware of good practices for models, such as hyperparameter tuning, transfer learning, and callbacks.
5. [ ] Be able to undertake distributed training.

## Prerequisites

We recommend that attendees have a working knowledge of Python, Linux, and HPC (High Performance Computing). If you need to learn any of these, then please consider attending the appropriate course:

- [SWD1a: Introduction to Python programming](https://arc.leeds.ac.uk/training/courses/swd1a/)
- [HPC0: Introduction to Linux for HPC](https://arc.leeds.ac.uk/training/courses/hpc0/)
- [HPC1: Introduction to High Performance Computing](https://arc.leeds.ac.uk/training/courses/hpc1/)

It is strongly recommended that you bring your own laptop to this workshop with some specific software installed. Further information will be provided when you are accepted onto the course.

## Duration

1 day

## Frequency

This workshop usually runs once each academic year. If you would like a bespoke version of this course run in your department, then please [contact us](https://bit.ly/arc-help).  

## Suitability

Research postgraduate students and above; teaching and lecturing staff.

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