After my last blog on the use of relational databases PostgreSQL and MonetDB to help compensate for R’s RAM limitations, I received an email from a reader… Read More »ff and Too-Big-for-Memory Data in R — Part III
Full title: Applied Stochastic Processes, Chaos Modeling, and Probabilistic Properties of Numeration Systems. An alternative title is Organized Chaos. Published June 2, 2018. Author: Vincent… Read More »Free Book: Applied Stochastic Processes
In the “Ecology of Metrics,” I wrote about “alignment” being a type of metric; alignment can measure the extent to which an organization’s supply or… Read More »Fugues of Operational Market Alignment
When the first release of Spark became available in 2014, Hadoop had already enjoyed several years of growth since 2009 onwards in the commercial space.… Read More »Why choose Apache Spark over Hadoop for your Big Data project?
The age of Artificial Intelligence (AI) is almost upon us. Rapid developments in machine learning have allowed us to build better, smarter machines that are… Read More »How Mobile AI Will Transform Our Lives
Enterprises are learning fast about the relevance and use of AI and Cognitive Computing platforms. Before adopting AI and Cognitive Computing platforms, enterprises must focus… Read More »Steps required before adopting AI & Cognitive Computing platform
This is a popular question recently posted on Quora, with my answer viewed more than 8,000 times so far. I am re-posting it here. This… Read More »What do mathematicians mean by good math and bad math?
What I discussed here is not only the math derivation which has usually been ignored in decision tree, but also the following question: what does… Read More »How to prove it in math: why deeper decision trees will never have higher expected cross entropy?
Guest blog post by David Enríquez Arriano. For more information or to get higher pictures resolution, contact the author (see contact information at the bottom… Read More »AI with Pyramids of Self Programmable Gates
A machine learning solution can be broadly divided into 3 parts. A typical ML exercise would involve experimentation and iteration of all the 3 parts… Read More »An ML Framework
