The course presents the concepts and techniques used to apply deep neural networks in applications such as computer vision and natural language processing. The organization of the course allows guiding students into the field of deep learning, starting from key concepts, such as learning algorithms and backpropagation, to advanced topics such as autoencoders and generative models.
The course is practical; therefore, the emphasis is in the efficient implementation of algorithms taught in lectures, with the support of high-level frameworks such as TensorFlow and Pytorch. At the end of the course, students will be in the capacity of programming application in high-level computer vision and natural language processing.
Doctor en Ciencias, Computación
Universidad de Chile