This lecture is an introduction to Machine Learning/Deep Learning. Students will gain foundational knowledge of Deep Learning algorithms emphasizing in the current state-of-the-art Neural Networks for Computer Vision: the Convolutional Neural Networks. Several examples on applications of these techniques will be also shown.
Note that two computer-aided Labs are dedicated to this topic with complementary aspects and applications,
1) One organized by Dr. Dirk Kruecker et al. (DESY and Hamburg University) on "Deep Learning with Keras I+II" with application to Particle Physics or to a more generix case (see Labs Table
2) The other one by Dr L. LLoret & Dr D. Tuccillo (UC and CSIC, SP) on "Machine Learning & Deep Learning applied to Astrophysics " (see Labs Table).