Which machine learning algorithm should I use?

Which machine learning (ML) algorithm should I use? It’s a common question I get asked and usually, once I know something about the application and the data I can make an educated guess: a clustering algorithm, a neural net, k-nearest neighbour… But, I’ve been working in ML for decades. For ML newbies this is a hard problem because there are so many ML algorithms to choose between. SAS have created a resource designed primarily for beginner to intermediate data scientists or analysts who are interested in identifying and applying machine learning algorithms to address the problems of their interest. Read their blog post to learn how to navigate their flow chart.


from The Universal Machine http://universal-machine.blogspot.com/2017/10/which-machine-learning-algorithm-should.html

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Machine learning: the power and promise of computers that learn by example

Machine Learning is becoming more important in many aspects of our daily lives. However, most of the general public and importantly politicians and policymakers are quite ignorant of its scope, strengths and weaknesses. To better inform people the UK’s prestigious Royal Society has recently released a report titled Machine learning: the power and promise of computers that learn by example.

from The Universal Machine http://universal-machine.blogspot.com/2017/10/machine-learning-power-and-promise-of.html

Says it all really!

from The Universal Machine http://universal-machine.blogspot.com/2017/10/says-it-all-really.html