  Faced with continuously increasing scale of data, original back-propagation
neural network based machine learning algorithm presents two non-trivial
challenges: huge amount of data makes it difficult to maintain both efficiency
and accuracy; redundant data aggravates the system workload. This project is
mainly focused on the solution to the issues above, combining deep learning
algorithm with cloud computing platform to deal with large-scale data. A
MapReduce-based handwriting character recognizer will be designed in this
project to verify the efficiency improvement this mechanism will achieve on
training and practical large-scale data. Careful discussion and experiment will
be developed to illustrate how deep learning algorithm works to train
handwritten digits data, how MapReduce is implemented on deep learning neural
network, and why this combination accelerates computation. Besides performance,
the scalability and robustness will be mentioned in this report as well. Our
system comes with two demonstration software that visually illustrates our
handwritten digit recognition/encoding application.
