New Book on Synthetic Data: Version 3.0 Just Released
Update on March 3, 2023: Version 4.0 has been released and now replaces version 3.0 on the e-Store. It contains a new full chapter on enhanced generative adversarial networks (GANs) with comparison to copula-based methods for data synthetization, with illustrations on real-life datasets. The book has considerably grown since version 1.0. It started with synthetic […]
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Math-free, Parameter-free Gradient Descent in Python
Entitled “Math-free, Parameter-free Gradient Descent in Python”, the full version in PDF format is accessible in the “Free Books and Articles” section, here. I discuss techniques related to the gradient descent method in 2D. The goal is to find the minima of a target function, called the cost function. The values of the function are computed at […]
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New Interpolation Methods for Data Synthetization and Prediction
Entitled “New Interpolation Methods for Synthetization and Prediction”, the full version in PDF format is accessible in the “Free Books and Articles” section, here. This article is an extract from my book “Synthetic Data and Generative AI”, available here. I describe little-known original interpolation methods with applications to real-life datasets. These simple techniques are easy to implement and can […]
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Empirical Optimization with Divergent Fixed Point Algorithm – When All Else Fails
Entitled “Empirical Optimization with Divergent Fixed Point Algorithm – When All Else Fails”, the full version in PDF format is accessible in the “Free Books and Articles” section, here. Also discussed in details with Python code in my book “Synthetic Data”, available here. While the technique discussed here is a last resort solution when all else fails, it is […]
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Course: Synthetic Data and Interpretable Machine Learning
This live course is based on my book “Synthetic Data”, available here. Participants will receive a free copy of this book. The information below provides a brief overview of the course. For enrollment or inquiries, follow this link. Course Description The performance of machine learning algorithms such as classification, clustering, regression, decision trees or neural networks […]
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New Book: Synthetic Data and Generative AI
Synthetic data is used more and more to augment real-life datasets, enriching them and allowing black-box systems to correctly classify observations or predict values that are well outside of training and validation sets. In addition, it helps understand decisions made by obscure systems such as deep neural networks, contributing to the development of explainable AI. […]
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Spectacular Videos: Synthetic Universes, with Star Collision Graph
Entitled “Spectacular Videos: Synthetic Universes, with Star Collision Graph”, the full version in PDF format is accessible in the “Free Books and Articles” section, here. Also discussed in details with Python code in my book “Synthetic Data”, available here. This project started as an attempt to generate simulations for the three-body problem in astronomy: studying the orbits of three […]
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Dynamic Clouds and Landscape Generation: Morphing and Evolutionary Processes
Entitled “Dynamic Clouds and Landscape Generation: Morphing and Evolutionary Processes”, the full version in PDF format is accessible in the “Free Books and Articles” section, here. Also discussed in details with Python code in my book “Synthetic Data”, available here. My previous article focused on map generation in 3D, and also features a fascinating video, see here. In this […]
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From 3D Contour Plots to AI-Generated Art
Fun tutorial to learn how to make professional contour plots in Python, with incredible animated visualizations. At the intersection of machine learning, scientific computing, automated art, cartography, and video games. Section 3 is particularly interesting, as it shows all the work behind the scene, to complete this project in 20 hours when you have no […]
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What is a Data Video, How to Produce One in Python, and Why
Watch this 6-min video, discussing one aspect of Explainable AI. It features a spectacular data video done in Python, applied to shape classification for meteorites, on synthetic data. This video is an extract from my course “Intuitive Machine Learning and explainable AI”, available here, based on the book with same title, available here. This video […]
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