19329401        
        
          Lecture        
      
      SoSe 19: Deep Learning
Tim Landgraf
Additional information / Pre-requisites
Übungen siehe 19329402
Comments
In recent years, deep neural networks have become the state-of-the-art solution for a multitude of tasks in computer vision, natural language processing and robotics. In the lecture we will introduce essential concepts such as convolutional neural networks, recurrent neural networks, generative models and deep reinforcement learning. The lectures will be accompanied by practical assignments using modern deep learning frameworks such as Tensorflow and PyTorch.
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12 Class schedule
Additional appointments
Tue, 2019-10-01 10:00 - 12:001. Klausur
    
    
    
          
          
            
              Fri, 2019-10-11 10:00 - 12:00            
                2. Klausur
    
    
    
          
          Regular appointments
                  
                    
                      Mon, 2019-09-23 10:00 - 12:00                    
                        
    
    
                  
                  
                    
                      Tue, 2019-09-24 10:00 - 12:00                    
                        
    
    
                  
                  
                    
                      Wed, 2019-09-25 10:00 - 12:00                    
                        
    
    
                  
                  
                    
                      Thu, 2019-09-26 10:00 - 12:00                    
                        
    
    
                  
                  
                    
                      Fri, 2019-09-27 10:00 - 12:00                    
                        
    
    
                  
                  
                    
                      Mon, 2019-09-30 10:00 - 12:00                    
                        
    
    
                  
                  
                    
                      Wed, 2019-10-02 10:00 - 12:00                    
                        
    
    
                  
                  
                    
                      Fri, 2019-10-04 10:00 - 12:00                    
                        
    
    
                  
                  
                    
                      Mon, 2019-10-07 10:00 - 12:00                    
                        
    
    
                  
                  
                    
                      Tue, 2019-10-08 10:00 - 12:00                    
                        
    
    
                  
                  
                    
                      Wed, 2019-10-09 10:00 - 12:00                    
                        
    
    
                  
                  
                    
                      Thu, 2019-10-10 10:00 - 12:00                    
                        
    
    
                  
                
              