Hands-on AI I provides a first direct contact with various AI approaches (no previous knowledge is required). The focus of this course is mainly put on Artificial Neural Networks and Deep Learning. Objectives are practical applications and getting an overview of Deep Learning approaches. All of the shown techniques will be taught in much greater detail later in the studies.
Subject
Handling and understanding of different kinds of data sets
Visualization, dimensionality reduction and clustering of data
Moving from Linear Regression to Logistic Regression and Artificial Neural Networks
Understanding gradient descent
Using Deep Learning frameworks like PyTorch
Playing around with the first Artificial Neural Networks
Introducing Convolutional Neural Networks
Tips and tricks for making networks learn (batch normalization, dropout, transfer learning, etc.)
Criteria for evaluation
Online Exams
Language
English
Changing subject?
No
Corresponding lecture
in collaboration with 536AIBAHO1U20: UE Hands-on AI I (1.5 ECTS) equivalent to 536AIBAHO1K19: KV Hands-on AI I (3 ECTS)
