Using Data Science and Google Cloud to Win March Madness…Well, Not Really
I suck at the NCAA March Madness® bracket selection process. I let my personal biases get in the way of making decisions based upon the numbers. I over-rate the well...
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K-nn Clustering Explained in One Picture
This is a simple overview of the k-NN process. Perhaps the most challenging step is finding a k that’s “just right”. The square root of n can put you i...
Top 8 Data Science Use Cases in Manufacturing
The manufacturing business faces huge transformations nowadays. Due to rapid development of digital world and broad application of data science, various fields of human a...
Is Robotic Process Automation (RPA) Really AI?
Summary: Based on a McKinsey study we reported that 47% of companies had at least one AI/ML implementation in place. Looking back at the data and the dominance of RPA...
March Madness, KenPom and Python/Pandas.
March Madness officially arrived at 6 PM CDT, Sunday 3/17/2019. 68 D1 schools — 32 league champions and 36 at large selections — received invitations to this ...
Can Lack of Data Always Provide Valuable Insights?
Can Lack of Data Always Provide Valuable Insights? Prashanth H Southekal and Matthew Joyce Today, data – both structured and unstructured, is seen as the most valuable ...
Can we fix Smart City deployments using AI, Cloud and Video?
Introduction I spoke at the iot expo on AI and smart cities in London this week Smart cities have been around for more than a decade The overall numbers for Smart citie...
Determining Sample Size in One Picture
Determining sample sizes is a challenging undertaking. For simplicity, I’ve limited this picture to the one of the most common testing situation: testing for differ...
Opening the black box of offline marketing with data analytics
Offline marketing is far from dead The marketing communication industry has three main players: the brand, the agency and the media owner. The agency, who is typically th...
15 Great Articles about Bayesian Methods and Networks
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...