This course is an introduction to Deep Learning. It motivates neural networks for solving non-linear decision boundary problems and introduces backpropagation and gradient descent for model fitting. Further topics are CNNs, RNNs, transfer learning and generative models (autoencoders and GAN). It is meant for beginners with little or no experience in the field. The material accelerates students to a point where they must complete their own deep learning project. The course is taught at DIS Copenhagen.
To get started:
- Open a terminal/console on your computer.
- Navigate to the directory where you keep the folder for this course
- Run
git clone https://github.com/ulfaslak/artificial_neural_networks_and_deep_learning
Now you have all the course files on your computer. When I update the course material (and I do every now and then) you can get the newest version of all the files by executing git pull origin master from inside the course folder in your terminal/console.
Important: All course information is posted on the wiki.