This course gives a practical introduction to deep learning, convolutional and recurrent neural networks, GPU computing, and tools to train and apply deep neural networks for natural language processing, images, and other applications.
The course consists of lectures and hands-on exercises. TensorFlow 2, Keras, and PyTorch will be used in the exercise sessions. CSC's Notebooks environment will be used on the first day of the course, and the new Puhti-AI partition on the second day.
After the course the participants should have the skills and knowledge needed to begin applying deep learning for different tasks and utilizing the GPU resources available at CSC for training and deploying their own neural networks.
The participants are assumed to have working knowledge of Python and suitable background in data analysis, machine learning, or a related field. Previous experience in deep learning is not required, but the fundamentals of machine learning are not covered on this course. Basic knowledge of a Linux/Unix environment will be assumed.
Day 1, Thursday 12.12
09.00 – 11.00 Introduction to deep learning and to Notebooks
11.00 – 12.00 Multi-layer perceptrons
12.00 – 13.00 Lunch
13.00 – 14.30 Image data and convolutional neural networks
14.30 – 16.00 Text data, recurrent neural networks, and attention
Day 2, Friday 13.12
09.00 – 10.30 Deep learning frameworks, GPUs, batch jobs
10.30 – 12.00 Image classification exercises
12.00 – 13.00 Lunch
13.00 – 14.00 Text categorization exercises
14.00 – 16.00 Cloud, using multiple GPUs
Coffee will be served both for the morning and afternoon sessions
Markus Koskela (CSC), Mats Sjöberg (CSC)
Language: English
Price: Free of charge
