Module 1, L2: remarks

In lecture 2, we will mainly learn about: 

• Basic building blocks in feedforward neural networks (neurons, activations, layers, etc). 
• Optimization based supervised learning (entropy loss, cross-entropy loss, etc). 

Most videos are from Andrew Ng's course in deep learning at Coursera, https://www.coursera.org/specializations/deep-learning, Links to an external site. but some are recorded by Lennart Svensson. We have also created a page with Reading directions. 

 

General advice: 

• The videos have intentional been trimmed (the start and end are sometimes omitted). 
• Sometimes the rest of the video appears later (say, after a small quiz) and we therefore recommend that you watch precisely the included part of each video. 
• Use the button "Next" or "Nästa" to move to the next video, quiz or page in the same lecture module. 
• Keep pen and paper ready to take notes, since this will help you stay alert.
• Pause the videos occasionally and try to summarise what you have learned. It is often with brief pause and you don't even need to write down the summary for this to affective. 
• Adjust the playback speed of the videos. Andrew Ng talks very slowly and 1.25 may be a reasonable alternative.

We apologize in advance for all the clicking that you will have to do to watch the videos and hope that you will still appreciate them.