Deep learning 1Laajuus (5 cr)

Objective

The student understands the basics of deep learning and neural networks and the limitations and opportunities related to teaching them. The student can apply the methods used in deep learning in the Pytorch environment.

Content

- Artificial neurons and neural networks - Deep learning with neural networks - Teaching neural networks - Use of trained neural networks - Hyperparameters of neural networks - Using the Pytorch environment - CNN neural networks (Convolutional Neural Networks) - RNN neural networks (Recurrent Neural Networks) - Basics of natural language processing (NLP).

Qualifications

Data science mathematics 1 (basic concepts of statistics) Data science mathematics 2 (matrix algebra) Python programming

Evaluation

Lectures (introductory lecture + lecture recordings) and exercises.