DEEP LEARNING
Introduce the basic principles of neural networks.
EXPECTED LEARNING OUTCOMES
KNOWLEDGE AND UNDERSTANDING SKILLS:
At the end of the teaching the student will have to:
-) understand what neural networks are;;
-) understand the differences between the different basic principles;
-) know the most important models.
APPLIED KNOWLEDGE AND UNDERSTANDING:
At the end of the teaching the student should be able to:
-) understand if a certain problem can be solved with a certain technique;
-) formalize a problem;
-) operate in the field of machine learning with neural networks.
COMMUNICATION SKILLS:
At the end of the teaching, the student should be able to expound on the concepts learned, using correct and precise language.
ABILITY TO LEARN:
At the end of the teaching the student should be able to read texts and research articles.
-) Introduction to machine learning;
-) introduction to neural networks;
-) examples and applications;
-) introduction to Python+Keras;
-) implementation of the examples in Keras.
-) Introduction to machine learning;
-) introduction to neural networks;
-) examples and applications;
-) introduction to Python+Keras;
-) implementation of the examples in Keras.
Notes from the course: ; Deep learning book: https://www.deeplearningbook.org/;
Neural networks and deep learning: http://neuralnetworksanddeeplearning.com/
Lectures.
Project.
E-mail: maurizio.parton@unich.it.
Mobile phone: 349-5323-199.