The 2014 Texata Big Data Analytics World Championships in October 2014 is a competition for students and professionals to develop and test their Big Data Analytics skills against their friends, colleagues and top data experts from around the world.
Dr. Kirk Borne discusses "Data Profiling – Four Steps to Knowing Your Big Data".
The four steps are:
1. Data Preview and Selection
2. Data Cleansing and Preparation
3. Feature Selection
4. Data Typing for Normalization and Transformation
Takashi Ozaki has a nice blog post comparing machine learning classifiers based on their hyperplanes or decision boundaries.
Compared: Decision Tree, Logistic Regression, SVM, Neural Net and Random Forrest.
It appears Random Forests work best when cluster boundaries are unknown.
RESEARCH COLLOQUIUM: CALL FOR PAPERS
LEGAL AND ETHICAL ISSUES IN PREDICTIVE DATA ANALYTICS
June 19 & 20, 2014
Abstract Submission Deadline: March 3, 2014
Creativity is the most important trait to look for in data scientists. Data, technology and skills are just the foundation. Competitive advantages result from creative data scientists, not "big data" or technologies or math and statistical skills.
At data science competition site Kaggle, those who do well “spend all their time being creative” as they comb through and pull ideas out of the data.
Moore’s new law is that big data will lead to big science. The Gordon and Betty Moore Foundation plans to give USD $1.5 million grants (in $200 000 to $300 000 yearly installments) to 15 worthy interdisciplinary scientists who can develop and use new algorithms, machine learning techniques, and other data-intensive science tricks to turn huge volumes of data into amazing scientific discoveries.
1. The hybrid data cloud.
2. Mobility is driving big data investment.
3. Big data can surround and enhance existing applications.
4. Internet of Things will make current big data projects look like small stuff.
5. Big innovation is coming to the front end of the data spectrum.