Data analytics, machine learning or artificial intelligence?
Are the terms data analytics, machine learning and artificial intelligence interchangeable or do they each describe a different process with a distinct purpose?
The border between Machine Learning (ML) and Artificial Intelligence (AI) is fuzzy. AI tries to get machines and systems to act intelligently, but what do we mean by intelligent? A well-known joke in the AI community is that if you ask ten AI practitioners ‘what is AI?’, you’ll get at least a dozen answers. Machine learning, on the other hand, is an AI system that can learn and change its behaviour based on learning. This is not just recording the information but generalising it and adapting behaviour accordingly.
Meanwhile, Data Analytics (DA) is primarily concerned with exploring large sets of data using a range of statistical, machine learning, visualisation, relational database tools and other techniques to find meaningful information. These tools are typically applied manually, as are the decisions resulting from the analysis outputs. If sequences of analysis are automated, this moves towards AI, blurring the boundaries further.
In this course, we will be concerned with ML and AI technologies and how they can be combined towards autonomous or supervised decision-making for business purposes. By guiding you to explore some basic machine learning and decision-making algorithms we will help you to explore and understand some of the benefits and limitations of ML and AI.
Read the four articles below and develop your own definition of AI and ML, indicating the difference between the two:
Machine Learning vs. AI, Important Differences Between Them (Iriondo 2018)
Share your definitions in the comments and respond to those posted by other learners.
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