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DEEP LEARNING ALGORITHMS

Machine learning can appear in many guises. We now discuss a number of applications, the types of data they deal with, and finally, we formalize the problems in a somewhat more stylized fashion. The latter is key if we want to avoid reinventing the wheel for every new application. Instead, much of the art of machine learning is to reduce a range of fairly disparate problems to a set of fairly narrow prototypes. Much of the science of machine learning is then to solve those problems and provide good guarantees for the solutions.

The dropbox folder contains exercises, research papers and industry cases that will be covered in Deep Learning Algorithms.

              

                 

                  is a coding software for statistical computing.                       Download here.

                    is a programming language.

                    Download here.

I have a blog titled review of different softwre packages.

Module 0:  Deep Learning Algorithm Modules

Module 1:  The evolution and application of deep learning methods

Module 2:  Statistical inference, machine learning and deep learning

Module 3:  Training a deep learning model

Module 4:  Deep learning for time series

Module 5:   Useful tools and packages

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