Implementieren Sie gebräuchliche Deep-Learning-Workflows in MATLAB® mit Bild- und Sequenzdaten aus der Praxis. Machen Sie sich mit den Konzepten von Deep-Learning-Algorithmen und Standard-Netzwerkarchitektur vertraut.
Get an overview of the course. Perform image classification using pretrained networks. Use transfer learning to train customized classification networks.
Understand how information is passed between network layers and how different types of layers work.
Train networks from scratch. Understand how training algorithms work. Set training options to monitor and control training.
Choose and implement modifications to training algorithm options and training data to improve network performance.
Bring together image classification concepts that you have learned with a project.
Create convolutional networks that can predict continuous numeric responses.
Train networks to locate and label specific objects within images.
Build and train networks to perform classification on ordered sequences of data, such as time series or sensor data.
Use recurrent networks to create sequences of predictions.
Bring together signal classification concepts that you have learned with a project.
Learn next steps and give feedback on the course.
Format:Kurs zum Selbststudium
Sprache:Deutsch
Erkunden Sie Daten und erstellen Sie prädiktive Modelle.
Erlernen Sie praktische Bildverarbeitungs-Workflows in MATLAB.
Meistern Sie die Grundlage der Entwicklung intelligenter Controller, die aus Erfahrungen lernen können.
Machen Sie die ersten Schritte mit Deep-Learning-Methoden für die Bilderkennung.