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Currently the hot topics in Machine Learning research and in real applications.

In general the following are fairly hot in machine learning and data science communities that are interested in modeling:

Deep learning: This seems to be breaking all benchmarks in accuracies in a variety of complex problems.
NLP: Understanding sentiment, sarcasm, urgency and summarizing free flowing text are being studied extensively.
Spectral methods and Kernel methods driven modeling methods are always hot problems.

From an engineering perspective, there is a lot of emphasis in building newer visualization tools and techniques. Of course, I see a new engineering model of big data every week.

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