Relationships

Author of Machine Curve, Christian Versloot, lays out the relationships between data structures, business, mathematics, artificial intelligence, and machine learning in the diagram below:

© 2017 Machine Curve

Versloot provides a detailed description of each main area of the diagram in his article. It is an excellent read when you have ample time to digest it. Here is a brief overview to keep handy during the course, as these terms will popup often:

• Data science is about bridging the gap between data technology and data driven problems by bringing a good technological understanding & business-/problem-oriented mentality to the table. (Vansloot 2017)
• Artificial intelligence is about making machines intelligent – the goals may vary from superintelligence to very task-specific intelligence. (Vansloot 2017)
• Machine learning is about learning from data without explicit human programming, but with human-configured features. (Vansloot 2017)
• Deep learning makes the feature learning process autonomous. For this, the field uses very complex algorithms. (Vansloot 2017)
• Big data is about the characteristics of the data – volume, velocity, variety, veracity (and maybe variability) – and the value it may provide, but less about technology. Big data may be applied within any field, like ecology, astronomy, meteorology, but also in business. Business analytics tends to focus on applying data about past events to a business problem in order to learn for the future. (Vansloot 2017)

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