Process mining is changing the way enterprises operate and manage their processes. It tells the process ‘as-is’ and ensures that enterprises and process owners have c...
Neuromancer Blues” is a series of posts where I would like the reader to find guidance about overall data science topics such as data wrangling, database connectivi...
Randomised algorithms are built on statistical features played by random numbers. Quicksort is a good example to illustrate this algorithm. For instance, in a class of ...
There are some expressions about data that are getting a bit tired: Data is the new oil; In God We Trust (all others must bring data); Buy data, sell high… Okay, yo...
The COVID-19 crisis has hammered home the importance for organizations to become more digital. And I suspect that most organizations are thinking that just means being ...
For the first time, I taught an AI for Cyber Security course at the University of Oxford. I referred to this paper from Johns Hopkins which covered Deep Neural networks f...
There are a few key differences between the Binomial, Poisson and Hypergeometric Distributions. These distributions are used in data science anywhere there are dichotom...
A Generative model aims to learn and understand a dataset’s true distribution and create new data from it using unsupervised learning. These models (such as StyleGAN) h...
This is the second of two articles about our recent participation in the Pandemic Response Hackathon. Our project (CoronaRank) was one of only 5 projects out of 230 submi...
Summary: Now that you have a little time for introspection, how about reviewing the performance of your chatbots. Chances are this lock down period has given you a litt...