We are very excited to announce that KAUST in collaboration with Iraya Energies will be hosting a virtual summer school on the use of Machine Learning for Natural Language Processing (NLP) specifically applied to geoscientific applications.
- Click here
Registration deadline - May 15 (GMT+3 8pm)
Notification of selected participants - May 21 (GMT+3 8pm)
- Final year BS.c. students
- MS.c. students
- Ph.D. Candidates
- Basic knowledge of Python
- Basic knowledge of Machine Learning
Day 1 - NLP fundamentals: data preprocessing and word embeddings;
“We will focus on how to preprocess text and convert words into meaningful numeric values. We will learn how to create our own word embeddings and how to use similarity analysis and word vector maths to evaluate the suitability of our embeddings to geoscientific NLP tasks and compare these with openly available premade embeddings.”
Day 2 - Active learning, NLP in production;
“We will focus on applying some machine learning active learning strategy to label data for your NLP applications. We will bring you through a use case of cleaning your own training dataset and apply techniques such as uncertainity or diversity sampling to help you identify the data that can make the difference in your training and will require manual labelling.”
Day 3 - Attention and Transformers.
“We will focus on advanced NLP models based on deep learning. We will dissect the BERT model and demonstrate the down-stream applications of sentiment analysis, machine translation and language inference.”
Meet the Instructors:
Day 1 – Dr. Claire Birnie
"Claire is a research scientist at KAUST specialising in ML applications to geoscientific problems. Previously a snowboard instructor, Claire has transitioned to teaching the computer to solve her geophysics tasks."
Day 2 - Dr. Francois Baillard
“Francois is the Chief Technology Officer in Iraya Energies. Beyond his serious job, he loves to spend the rest of his time relaxing at the beach building sandcastles with the family and hugging his cats.”
Day 3 - Prof. Xiangliang Zhang
“Xiangliang is an Associate Professor in Computer Science at KAUST, specializing in machine learning and data mining. Her mission is to enable computer machines to learn.”