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by Graham Williams
Duck Duck Go



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AI, Machine Learning, Data Science

20200223 GNU/Linux is a very productive platform for learning about, utilising, developing and deploying Machine Learning algorithms, Artificial Intelligence models and Data Science services (MLAIDS). It has been the platform of choice for developers for nearly 30 years.

The goal of this chapter is to share the power of this suite of technology to the general computer user, making the latest developments accessible.. Often technology gets dumbed down to achieve widespread use but it leads to little or to no understanding. Our aim is to simplify access to technology whist educating users along the way.

So what is Artificial Intelligence? Many definitions exist and have changed over time, often to incorporate some latest technology that needs a marketing boost! It's useful to go back to the origins from a workshop in 1956 at Dartmouth College in the USA funded by the Rockefeller Foundation. The workshop agreed on the term artificial intelligence and proposed that it encapsulated “an attempt to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. … For the present purpose the artificial intelligence problem is taken to be that of making a machine behave in ways that would be called intelligent if a human were so behaving.

That's quite broad but we note that machine learning is a key element, as is language, and alluding to knowledge representation as abstractions and concepts, with a purpose of problem solving. Learning of course is also core to the human experience of intelligence.

Data Science, which as a term has gained currency since 2014, is a profession oriented endeavour of using both Machine Learning and AI technology (plus Statistics) to deliver new insights and knowledge from data.

This chapter highlights this exciting area of technological development in the context of GNU/Linux as an enabling operating system. The MLHub will be utilised as the platform through which AI, machine learning and data science are explored. The MLHub, put simply, aims to share the latest algorithms and models within a framework that is easy for people to build the models to share and a platform that is easy for anyone to explore.


Subsections
Support further development by purchasing the PDF version of the book.
Other online resources include the Data Science Desktop Survival Guide.
Books available on Amazon include Data Mining with Rattle and Essentials of Data Science.
Popular open source software includes rattle and wajig.
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