Deep Learning — Andreas Geiger - Deep Learning - Lecture 5.5 (Regularization: Data Augmentation)
Master Deep Learning: From Basics to Advanced AI Models
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6 learners
What you'll learn
Design and implement feedforward and convolutional neural networks using modern frameworks
Apply backpropagation and gradient-based optimization algorithms to train deep learning models
Implement and compare regularization techniques to improve model generalization
Construct and apply sequence models like RNNs for natural language processing tasks
This course includes
21.5 hours of video
Certificate of completion
Access on mobile and TV
Summary
Full Transcript
Lecture: Deep Learning (Prof. Andreas Geiger, University of Tübingen)
Course Website with Slides, Lecture Notes, Problems and Solutions:
https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/autonomous-vision/lectures/deep-learning/
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