It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data.
It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data.
The task of AI research is to use computation to model intelligent behavior, like collaboration.
Later on in the plan — if it becomes clear that the robot will need a detailed map of the fridge's middle shelf, to be able to reach for a jar of pickles, for example — it will refine its model as necessary, using valuable computation power to model only those areas crucial to the task at hand.
Which is ironic, given that we are more connected to information than we have ever been before, and the computation necessary to model problems has never been cheaper.
A new viewpoint will be required to take advantage of the information in heterochronous microsatellite data, for example by applying approximate Bayesian computation (ABC) to model and test potential demographic scenarios e.g., [58].
This reduces the computational burden from 5 × 10 = 50 model computations to 5 + 10 = 15 model computations, and is found to be sufficient for model selection in similar work (22).
Grid computation to test model assumptions is also developed for these two types of models.
It is easy, by simple computations, to conclude that model (5) has a unique disease-free equilibrium, (E_{0}= 0,0)).
The systematic analysis of transcription start sites and/or alternative splicing would obviously require the incorporation of the whole-genome sequence, provided that it is available for a given organism, and the development of heavy computations to build mRNA models accounting for alternative transcription and/or splicing.
