Irish Centre for High-End Computing (ICHEC) – Practical Deep Learning
Day 5 – Foundations of Data Science II (Friday 10th December)
9.30am-5.00pm: Irish Centre for High-End Computing (ICHEC)
Title: Practical Deep Learning
Brief synopsis: Sessions will consists of a mix of talks and hands-on sessions on the practical implementation of basic Deep Learning workflows and analyses. Topics to be covered will include the frameworks, tools and resources that are commonly available (e.g. Keras, Tensorflow), data preparation, model training/testing and inference. The sessions will also highlight common pitfalls (e.g. overfitting) and their implications in training Deep Learning models.
Participants will require laptops for both the course material and hands-on exercises, which will be distributed as Jupyter Notebooks. Hence participants should install on their laptop Python 3 along with the following packages: TensorFlow 2 plus recent releases of numpy, matplotlib, jupyter, ipykernel and scikit-learn. Participants could also install the latest Anaconda environment with all the default packages (https://www.anaconda.com/products/individual) to meet the requirements above.
Dr. Adam Ralph is a computational/data scientist at the Irish Centre for High-End Computing (ICHEC), the national centre for High-Performance Computing (HPC) in Ireland. His background is in mathematics and he’s part of the data science group at ICHEC, where he has been responsible for much of ICHEC’s teaching activities on various subjects, from scientific programming, data analysis tools such as R and machine/deep learning techniques.
Dr. Bruno Voisin is a Senior Data Scientist at the Irish Centre for High-End Computing (ICHEC), the national centre for High-Performance Computing (HPC) in Ireland. His background is in astrophysics having obtained a PhD in France based on research on data mining approaches for catalogue cross-referencing. Since joining ICHEC in 2008, he leads its data science activity that provides expertise and training to research groups, public sector agencies and industrial partners. He has worked on a diverse range of data science projects in areas from medical device development, risk modelling, digital humanities to more recent work that takes advantage of machine and deep learning techniques.
The SFI Centre for Research Training in Foundations of Data Science will train a cohort of PhD students with world-class foundational understanding in the horizontal themes of Applied Mathematics, Statistics, and Machine Learning.
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