Riskprep Blog - PRM Exam Preparation, PRM Test Qustions, PRMIA Sample ExamsMachine learning and data analytics
Machine learning and data analytics are quite 'hot' these days, particularly as they are increasingly being applied to economics and finance. A number of companies are using advanced analytics and data mining for creating new applications for finance. I stumbled upon one today - http://www.benchmarksolutions.com/ - that uses analytics to provide pricing for sparsely traded corporate bonds.
What all of this is about is really to use computers to solve problems - predict a value, or classify something given other known information. The simplest example of using data mining and analytics is of course linear regression, something those studying for the PRM exam are quite familiar with. But there are other advanced algorithms as well including neural networks and many others such as nearest neighbors, association rules, naive Bayes etc.
I am no expert on machine learning, but the point of this post is to provide a link to a free online machine learning course provided by Stanford's business school: http://www.ml-class.org. You will notice the course is officially over, but the material including the videos are all there and if this interests you, I think you will find it rewarding.
Machine learning and data analytics are quite 'hot' these days, particularly as they are increasingly being applied to economics and finance. A number of companies are using advanced analytics and data mining for creating new applications for finance. I stumbled upon one today - http://www.benchmarksolutions.com/ - that uses analytics to provide pricing for sparsely traded corporate bonds.
What all of this is about is really to use computers to solve problems - predict a value, or classify something given other known information. The simplest example of using data mining and analytics is of course linear regression, something those studying for the PRM exam are quite familiar with. But there are other advanced algorithms as well including neural networks and many others such as nearest neighbors, association rules, naive Bayes etc.
I am no expert on machine learning, but the point of this post is to provide a link to a free online machine learning course provided by Stanford's business school: http://www.ml-class.org. You will notice the course is officially over, but the material including the videos are all there and if this interests you, I think you will find it rewarding.
|