Deep Learning for managers

• Non-technical, but informative introduction to deep learning (=neural networks), similarities and differences to classical machine learning techniques
• Important concepts of deep learning: architecture of neural networks (nodes and layers for building complex networks), performance assessment, and tuning of neural networks
• Different types of deep learning: standard (feedforward) neural networks for structured data (e.g. in csv format), convolutional neural networks (e.g. for image/video processing), recurrent neural networks (e.g. for text analysis of social media and natural language processing), generative adversarial networks (e.g. for synthetic data generation, art, etc.)
• One-click deep learning for beginners: automatic network search and parameter selection
• Business cases and practical examples with real data using graphical interfaces in the machine learning platform BigML.com – no programming required!

Top speaker

• Amir Tabakovic – Strategist, Innovator, Investor in ML Technology, Chair of Expert Group Data Privacy and AI at Mobey Forum, Guest lecturer at ICEMD and ESADE

Subject Area Co-ordinator

• Prof. Dr. Michael Burkert, University of Fribourg