Business Analytics, Predictive Modeling, Data Mining, Statistical Programming, Vizualization, Statistical Consulting, Artificial Intelligence, Computer Science, Teaching
currently working in Business Analytics space, using tools and techniques to solve business critical problems, did masters from a central university of India in Industrial mathematics with strong exposure in Computer Science & Mathematics, looking forward to work in more advanced areas in Data Mining, Text Mining & Speech Mining..
What important truth do very few people agree with you on?
For folks who desire to have fun playing with data and develop both strong technical ability and skills to apply data science and analytic results to critical business issues.
A data scientist is somebody who can play with data, spot trends and learn truths few others know. Data scientists are inquisitive: exploring, asking questions, doing “what if” analysis, questioning existing assumptions and processes.
Data Science: the analysis of data creation. The data scientist has a solid foundation in computer science, modeling, statistics, analytics, math and strong business acumen, coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge.
Business Analytics: the practice of iterative, methodical exploration of an organization’s data with emphasis on statistical analysis.
...as I said - right now I would be interested to try a PMML file that's describing an ANN using only logistic activation functions. Why KNIME doesn't load the one you uploaded is clear (see my earlier post).
sorry for the late reply - AnalyticBridge was down for a while. It looks like our MLP does not support mixed activitation functions, which should be fixable easily in the next version. However, I am curious to see if this transwer in principle works: could you create an ANN in STATISTICA that is using only logistic functions and see if you can upload that PMML file in KNIME (or send it to us so we can try)?