GRADnet Machine learning and AI workshop

15 Jan 2020, 09:00 → 16 Jan 2020, 17:15 Europe/London

LT (Arts II)

A Bevan (Queen Mary), A Pourtsidou (Queen Mary), Marcella Bona (QMUL), U Blumenschein (Queen Mary)

This is a 2-day workshop that consists of a series of presentations and tutorials, to ensure delegates get the chance to learn about modern methods, and have the opportunity to get some hands on experience. This workshop will be of interests to PhD students keen to learn about, and start using modern data science and AI in the context of physics and astronomy.

Wednesday 15 January

10:30 Break

Introduction and Orientation Session

This session will lay down the housekeeping rules and provide some brief data wrangling issues.

1 Welcome and housekeeping

Speaker: Dr A Bevan (Queen Mary)

Slides Housekeeping.pdf

2 Why is data wrangling important?

Speaker: Dr Nick Barlow (Alan Turing Institute)

Slides DataWrangling_QMUL_150120.pdf

3 Data wrangling exercises

Speaker: Dr Nick Barlow (Alan Turing Institute)

Slides https://github.com/nbarlowATI/DataWranglingWorkshop https://github.com/wrattler/wrattler-examples

12:30 Lunch

Tutorial

4 Introduction to Python and TensorFlow (linear regression and neural network examples)

Speakers: Dr A Bevan (Queen Mary), JMM Davies (Queen Mary), Dr Marcella Bona (QMUL), TP Charman (Queen Mary)

Slides

• DecisionTrees.pdf
• https://github.com/adrianbevan/GRADnet-ML/tree/master/NN
• NNs.pdf
• NNs_Tutorial.pdf

15:00 Break

Plenary

5 Reinforcement learning

Speaker: Dr A Pourtsidou (Queen Mary)

Slides RL-lecture-AP.pdf

6 Sci ML team @ RAL

Speaker: Dr Jeyan Thiyagalingam (STFC)

Slides 2020_01_15_SciML_QMUL_GradNet_Jeyan.pdf

18:00 Dinner

Thursday 16 January

Tutorial

7 Linear regression, neural network model building, and decision trees (tutorial using SciKit Learn and Keras)

Speakers: Dr A Bevan (Queen Mary), JMM Davies (Queen Mary), Dr Marcella Bona (QMUL), TP Charman (Queen Mary)

Slides

• DecisionTrees.pdf
• gradnet_ml.pdf
• https://github.com/adrianbevan/GRADnet-ML/tree/master/Pulsars
• NNs.pdf

10:30 Break

Plenary

8 NNPDF - using neural networks to compute parton density functions

Speaker: Dr Maria Ubiali (DAMPT)

Slides NNPDF.pdf

9 ABBA - Automatically Building Better Algorithms.

Speaker: Dr John Woodward (QMUL)

Slides john_20200116.pdf john_20200116.pptx

12:30 Lunch

Tutorial

10 SQL tutorial

Speaker: Dr A Pourtsidou (Queen Mary)

Slides https://github.com/Alkistis/DSI/blob/master/SQL-tutorial-DSI.ipynb SQL.pdf

11 Data in finance

Speaker: Dr Thomas Babbedge (Gresham Investment Management LLC)

15:00 Break

Plenary

12 Challenges of Machine Learning in Physics

Speaker: Dr A Bevan (Queen Mary)

Slides 2020-GRADnet-ML-PhysicsChallenges.pdf

13 Machine Learning applied to neutrino physics

Speaker: Dr Sophie King (Kings College London)

Slides 20_01_16_ml_nu.pdf