About this blog

I opened this blog with 7 goals in mind:

• To have fun by detecting the signal in the data
• Explain how to use some machine learning algorithms using R & Python
• Engage non-scientific readers with the use of some outlier detection approaches
• Explain as clear as possible the main outlier detection algorithms
• Share new or existing methods for outlier analysis
• Externalize thoughts to clarify my own ideas
• Find people working in the same field or that share interest in the analysis of data. 

Recently, i finished my Ph.D. at the École de Technologie Supérieure (Montreal, Canada). One my main interests is the identification of outliers. Overall, i like to work with different types of machine learning algorithms.

Publications

• Pasillas‐Díaz, J. R., & Ratté, S. (2016). Bagged Subspaces for Unsupervised Outlier Detection. Computational Intelligence.  http://dx.doi.org/10.1111/coin.12097
• Pasillas‐Díaz, J. R., & Ratté, S. (2016). An unsupervised approach for combining scores of outlier detection techniques. Electronic Notes in Theoretical Computer Science 329, 61-77 http://dx.doi.org/10.1016/j.entcs.2016.12.005

A little more about me:
https://ca.linkedin.com/in/joseramonpasillasdiaz

José Ramón Pasillas Díaz

Some of my certifications (only those in Coursera):
https://www.coursera.org/user/a5b16f8a9100df4f79e8e64b8dd10b46

alfa2plus@hotmail.com

Let's dig into data! 

José Ramón Pasillas Díaz