In our two-day workshop, you will acquire basic knowledge about Artificial Intelligence (AI) and Deep Learning and learn how to use Deep Learning to solve numerous problems, such as the churn prediction use case and image classification tasks.
We will begin by presenting an intuitive introduction to how neural networks function, then provide an overview of common architectures that can be used to solve a variety of problems. You will also learn how to organise your deep learning projects and how to use modern tools such as PyTorch, TensorBoard and PyTorch Lightning to your benefit. After completing this workshop, you will be able to use Deep Learning independently to solve problems.
- How do neuronal networks learn?
- Learn the math for feedforward neural networks
- PyTorch basics
- Processing data in PyTorch
- Feedforward network training and evaluation
- Understanding common problems with neuronal networks
- Transferring PyTorch to PyTorch Lightning
- Table-based data modelling with neural networks
- Understanding Convolutional Neural Networks (CNN) and the related architectures
- Image classification with CNN and transfer learning
- Sequence modelling for time series
- Tips and tricks for modelling neuronal networks
- Overview of advanced neuronal network architectures
The workshop has been developed for
- Experts, e.g. IT staff, team leaders, project managers, process owners, innovation managers
- Software developers and data engineers
- Data scientists
- Basic knowledge of Python, linear algebra and probability theory