Cybersecurity Use Case: AI Agent for Anomaly Detection – Part 2
In the first part of this series, here, I feature a click fraud case that we are working on, litigated by one of the largest law firms in the US. The input data comes from an Excel repository, automatically processed by an AI agent part of our BondingAI enterprise solutions. It comes with insights generation […]
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Cybersecurity Use Case: AI Agent for Anomaly Detection – Part 1
The case discussed here concerns fraudulent paid clicks to defraud a Google advertiser. The sophisticated click fraud scheme involving clicking viruses, data centers and other means, is undetected by Google. I worked with the law firm involved in the litigation, to build an agent able to pinpoint the sources of fraudulent traffic. The agent processes […]
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Synthesizing Multi-Table Databases: Model Evaluation & Vendor Comparison
Synthesizing multi-table tabular data presents its own challenges, compared to single-table. When the database contains date columns such as transaction or admission date, a frequent occurrence in real-world datasets, generating high quality synthetizations and model evaluation are even more complicated. In this article, we focus on this type of problems, comparing generated observations produced by […]
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New Book: State of the Art in GenAI & LLMs — Creative Projects, with Solutions
With 23 top projects, 96 subprojects, and 6000 lines of Python code, this vendor-neutral coursebook is a goldmine for any analytic professional or AI/ML engineer interested in developing superior GenAI or LLM enterprise apps using ground-breaking technology. This is not another book discussing the same topics that you learn in bootcamps, college classes, Coursera, or […]
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Probabilistic Nearest Neighbor Search: The Swiss Army Knife of GenAI
ANN — Approximate Nearest Neighbors — is at the core of fast vector search, itself central to GenAI, especially GPT and LLM. My new methodology, abbreviated as PANN, has many other applications: clustering, classification, measuring the similarity between two datasets (images, soundtracks, time series, and so on), tabular data synthetization (improving poor synthetizations), model evaluation, […]
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Synthesizing Geospatial Data with A Simple NoGAN Technique
If you regularly read my articles, you know that I developed several different techniques for data synthetization. Many are explained in details in my upcoming book Synthetic Data and Generative AI (Elsevier), available here. It includes generative adversarial networks (GANs), copulas, agent-based modeling, methods based on interpolation, correlated noise mixtures, and more. The technique presented […]
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Sound Generation in Python: Turning Your Data into Music
Not long ago, I published here an article entitled “The Sound that Data Makes”. The goal was turning data — random noise in this case — into music. The hope was that by “listening” to your data, you could gain a different kind of insights, not conveyed by visualizations or tabular summaries. This article is […]
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A Synthetic Stock Exchange Played with Real Money
Not only that, but you can predict — more precisely compute with absolute certainty — what the value of any stock will be tomorrow. Transaction fees are well below 0.05% and the market, at least in the version presented here, is fair: in other words, a zero-sum game if you play by luck. If instead […]
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Introduction to Discrete Chaotic Dynamical Systems
Entitled “Introduction to Discrete Chaotic Dynamical Systems”, the full version in PDF format is accessible in the “Free Books and Articles” section, here. This article is an extract from my book “Gentle Introduction to Chaotic Dynamical Systems”, available here. This is chapter 2 of my upcoming book on dynamical systems and related stochastic processes, expected to be […]
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Random Walks, Brownian Motions, and Related Stochastic Processes
Entitled “Random Walks, Brownian Motions, and Related Stochastic Processes”, the full version in PDF format is accessible in the “Free Books and Articles” section, here. This article is an extract from my book “Gentle Introduction to Chaotic Dynamical Systems”, available here. In about 15 pages, this scratch course covers a lot more material than expected in such […]
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