Hi scikit, Here I am proposing to work on deep learning topic for GSOC 2013. Deep learning is a relatively new research area that is progressing fast with a lot of potential for contributions. It involves an intersting idea by trying to imitate the brain, as it uses many levels (hidden layers) of processing. Where the levels are at decreasing order of abstractions!
In this project, I'm planning to work on each step carefully, first I look into "Deep Boltzmann machines", then "Deep belief networks","Deep auto-encoders", "Stacked denoising auto-encoders", and more. I could create a complete plan for this, once I get your feedback :) I have been involved in quite a number of machine learning projects, from dealing with imbalanced datasets (software quality prediction), to XML classification, from recognizing gender out of handwriting, to breast cancer prediction using mammograms. I'm in my second semester as a graduate student (MSc), and machine learning is my research area. My thesis would involve deep learning, which i will apply on bioinformatics and face recognition. I would be more than happy to work with a mentor on this! Thank you! Best regards, --Issam Laradji ------------------------------------------------------------------------------ Precog is a next-generation analytics platform capable of advanced analytics on semi-structured data. The platform includes APIs for building apps and a phenomenal toolset for data science. Developers can use our toolset for easy data analysis & visualization. Get a free account! http://www2.precog.com/precogplatform/slashdotnewsletter _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
