An Empirical Proof of the Riemann Conjecture
The correct term should be heuristic proof. It is not a formal proof from a mathematical point of view, but strong arguments based on empirical… Read More »An Empirical Proof of the Riemann Conjecture
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The Mathematics of AI
The mathematics rubric includes articles that focus primarily upon the mathematical underpinnings of machine learning, data analytics and cognitive computing. These articles either cover mathematical notation extensively or deal with mathematical principles that influence the code and models used in data science.
New Military-grade Random Bit Sequences Based on Irrational Numbers and Fast Computations
Irrational numbers such as π may have been the first ones used to create perfect randomness and strong cryptographic systems. They were also among the… Read More »New Military-grade Random Bit Sequences Based on Irrational Numbers and Fast Computations
New Book: Synthetic Data – Generation and Applications
Synthetic data is used more and more to augment real-life datasets. It enriches them and allow black-box systems to correctly classify observations or predict values… Read More »New Book: Synthetic Data – Generation and Applications
AlphaTensor and Its Implications for AI, Reinforcement Learning, and Science
The issue is not just the actual multiplication but the fastest method to perform the multiplication. The speeding up of matrix multiplication calculations has a high impact because matrix multiplication is a part of many applications – especially in deep learning and image processing.
Video: Introduction to Machine Learning
This 30 minutes video features my interview about the upcoming course “Intuitive Machine Learning”, based on my new book with the same title. Hosted by… Read More »Video: Introduction to Machine Learning
We Live in a Bayesian World
“Fail fast, pivot, and try again” is the heart of learning. And in knowledge-based industries, the economies of learning are more powerful than the economies… Read More »We Live in a Bayesian World
Understanding the Value of Bayesian Networks
Machine learning algorithms are based on correlation – they do not specify cause and effect relations. Increasingly, Hence, Causality (cause and effect relations) is an… Read More »Understanding the Value of Bayesian Networks
The Riemann Hypothesis in One Picture
I wrote this article for machine learning and analytic professionals in general. Actually, I describe a new visual, simple, intuitive method for supervised classification. It… Read More »The Riemann Hypothesis in One Picture
DSC Podcast Series – Why and How to Partner Machine Learning with Math Optimization.mp4
Machine learning and deep learning have become standard tools in a data scientist’s toolbox, applied to generate insights into large amounts of data. But organizations… Read More »DSC Podcast Series – Why and How to Partner Machine Learning with Math Optimization.mp4
DSC Podcast Series – Navigating Decision Trade offs – Scratching the Surface with Math Optimization.mp4
As business decisions are becoming more and more complicated, Decision Analytics are becoming increasingly important and a way analytics teams can differentiate themselves from the… Read More »DSC Podcast Series – Navigating Decision Trade offs – Scratching the Surface with Math Optimization.mp4