About this event

This workshop builds on the Introduction to Data Analysis in Python course to start to learn how to answer more intricate questions about your data. It serves as an introduction to machine learning and, using scikit-learn you will discover about some of the algorithms available to you from linear regression through to k-nearest-neighbours.

Please look at our Code of Conduct which we follow at all virtual and in-person events.

Advanced requirements/set up:

Please bring along your own laptop. It will be taught in JupyterLab using the notebook interface and so before the session we recommend installing Anaconda Python.

We are running an in-person and online JGI drop-in installation session on Monday 3rd June from 11:15-12:30 - if you require any help in installing any software please attend this session.

Audience Level:

You should have a good grasp of the basics of the Python language and some experience with data manipulation and visualisation as taught in the Introduction to Data Analysis in Python course.

Learning Outcomes:

• Understand what machine learning is and what problems it can solve
• Be able to use scikit-learn to create machine learning pipelines
• Understand how to deal with overfitting

Instructors

Dr Richard Lane, Data Scientist, Jean Golding Institute

Dr Léo Gorman Data Scientist, Jean Golding Institute 

Left to right: Richard Lane, Léo Gorman

Dr Richard Lane (he/him)

Richard is a Data Scientist at the JGI. His interests are software development and processes for data science, delivering and designing training courses, and reproducible research. He has worked on computer vision of forensic and medical CT scans and data analysis from smart wearables. He manages the Ask-JGI helpdesk PhD data scientists, having worked on the team himself during his time as a PhD student in the School of Physics, before joining the Jean Golding Institute in 2023.

Dr Léo Gorman (he/him)

Léo is a Data Scientist at the JGI. He is interested in developing sustainable software for data management and analysis. He also has a keen interest in Bayesian analysis methods and multi-level modelling. Léo has experience applying data science in the field of international development. In collaboration with the International Livestock Research Institute, he has developed software and analytical procedures to help researchers better understand the issues facing smallholder farmers in Lower- and Middle-Income Countries. With a background in physics and international development, he joined the Jean Golding Institute in October 2023, after finishing his PhD at the Alan Turing Institute and the University of Bristol.

Bristol Data Week 2024

This event is part of Bristol Data Week 2024, organised by the Jean Golding Institute. Running from Monday 3rd June – Friday 7th June 2024, this will be our 7th annual Data Week; an interactive programme of speakers, training and workshops open to all and completely free of charge.

Keep up to date with sessions happening throughout Bristol Data Week on the Jean Golding Institute website follow us on Twitter @JGIBristol and use #BristolDataWeek.