AI for People and Business is an AI book and AI strategy framework. Here’s the official book trailer where I explain important topics that are covered in the book, ...
Summary: Things are getting repetitious and that can be boring. Still, looking at lessons from the 90s it’s clear there are at least one or two decades of important...
The covariance matrix has many interesting properties, and it can be found in mixture models, component analysis, Kalman filters, and more. Developing an intuition for ho...
How COVID-19 is Changing our Relationship with Data An increasing proportion of businesses use scientific methods to analyze data. Yet, because key decision-makers do not...
You might have seen how technologies are serving us in multiple fields and situations whether it is Artificial intelligence, ML or Blockchain. Technologies like artificia...
A recent article in BusinessWeek titled “Farmers Fight John Deere Over Who Gets to Fix an $800,000 Tractor” highlights a key challenge with which organizations must w...
Visualization has become a key application of data science in the telecommunications industry. Specifically, telecommunication analysis is highly dependent on the use of ...
P-values and critical values are so similar that they are often confused. They both do the same thing: enable you to support or reject the null hypothesis in a test. But ...
Scaling AI with Dynamic Inference Paths in Neural Networks Introduction IBM Research, with the help of the University of Texas Austin and the University of Maryland, has ...
Table of contents: What is Deep Learning? Supervised DL: The KISS Pathway That Leads To The Expected Unsupervised Deep Learning: An Exploratory Journey To Figuring Out th...