"neuroscience as a source of inspiration for data science", annina neumann, head of data...
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Neuroscience as a Source of Inspiration for Data Science?Data Natives ConferenceBerlin, 19. November 2015
Dr. Annina NeumannHead of Data ScienceBusiness Unit Big [email protected]
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Some Basics of Neuroscience
Parietal Lobe• Movement• Orientation• Recognition • Perception of stimuli
Frontal Lobe• Reasoning• Planning• Parts of speech• Movement• Emotions • Problem solving
Occipital Lobe • Visual processing
Temporal Lobe• Perception & recognition
of auditory stimuli • Memory• Speech
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A few crossing points between Neuroscience and Data Science
Behaviourism
Turing Machine and Finite Automaton
Classical Cognitive Science
Connectionism
Neural Networks Reinforcement Learning
…and it goes on
NeuroscienceCognitive Science
Data ScienceMachine Learning
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Connectionism challenges Classicism
Connectionism Neural Networks
1980s Parallel distributed processing
→ Connectionism
Use of computers to simulate neural processes
Classical Cognitive Science
?
Turing Machine
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Neural Coding Application
Grandmother Cells
Sparse vs. Distributed
Coding
• Sparse Coding Algorithms are often applied, e.g. in image processing and audio processing
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• Sparse Coding can be used in the concepts of „deep learning“ where compact features are learned from data
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A few crossing points between Neuroscience and Data Science
Behaviourism
Turing Machine and Finite Automaton
Classical Cognitive Science
Connectionism
Neural Networks Reinforcement Learning
…and it goes on
NeuroscienceCognitive Science
Data ScienceMachine Learning
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Back to the beginning…
Behaviourism
Neural Networks
Reinfocement Learning
Reinforcement learning
An area of machine learning that is concerned with:
How should an agent take actions in an environment so
that it can maximize its cumulative rewards?
http://hubpages.com/education/Psychology-and-Television-The-Big-Bang-Theory-Tackles-Operant-Conditioning
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Diskussion
Summary
• Neuroscience invesitgates the brain and its processes, like learning and reasoning
• In Data Science we use a lot if these findings, e.g. by applying machine learning algorithms to business problems and „real world“ data
• Neuroscience has been a great source of inspiration for Data Science – and vice versa!
• Many more opportunities and open questions!• For example: The humunculus, rules and decision-making Þ smart algorithms cannot replace data scientists yet!
Conclusion
Outlook
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Thank you!
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Dr. Annina NeumannHead of Data ScienceBusiness Unit Big [email protected]
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