Welcome to "Machine Learning" 

Welcome to the Canvas Page for our Machine Learning Applications course starting Week 36, 2024! This course primarily focuses on the applied aspects of machine learning, with a special emphasis on neural networks and deep learning.

Throughout this course, we will begin with an introduction to the basics of machine learning and provide a comprehensive overview of neural networks. We'll explore the perceptron as a fundamental element for linear separability, discuss its limitations in classification, and examine various activation functions and the sigmoid perceptron to address non-linear classification challenges.

We will also delve into different machine learning paradigms including supervised, unsupervised, and reinforcement learning. Key topics such as feed-forward neural networks and the backpropagation algorithm will be presented in detail. Additionally, we will cover recurrent neural networks (RNNs) to enhance your understanding of dynamic neural systems.

Our journey will culminate in a thorough discussion on deep learning, focusing on its fundamental principles and various types of neural networks utilized in deep learning applications.

I look forward to guiding you through these exciting topics and helping you harness the power of machine learning to solve real-world problems. Let’s embark on this learning adventure together!

Please consider the Course Handbook for more details.

Best regards,

Arend

	Course Syllabus			Contact information
				Arend Hintze Course Responsible  Teaching Professor ahz@du.se
				Hasan Fleyeh Teaching Professor hfl@du.se
				Juveria Shah TA, Lab responsible  juh@du.se