Deep Learning (XM_0083)

Based on lectures. I got a 9 for the exam! Deep learning becomes the leading learning and modeling paradigm in machine learning. During this course, we will present basic components of deep learning, such as: - different layers (e.g., linear layers, convolutional layers, pooling layers, recurrent layers); - non-linear activation functions (e.g., sigmoid, ReLU); - backpropagation; - learning algorithms (e.g., ADAM); - other (e.g., dropout). Further, we will show how to build deep ar...

Those are the notes I made during the whole course, it is not a summary! As long as you understand this document you do not need to watch any lecture. With those notes I have passed the course with a 7.5.

Those are the notes I made during the whole course, it is not a summary! As long as you understand this document you do not need to watch any lecture. With those notes I have passed the course with a 7.5.