Data Sets - Machine Learning Techniques

Data Sets Explainable AI Featured Posts Generative AI Machine Learning Synthetic Data

New Python Library to Evaluate AI-generated Data and Compare Models

Called GenAI-Evalution, you use it for instance to assess the quality of tabular synthetic data. In this case, it measures how faithfully the synthetization mimics the real data it is derived from, by comparing the full joint empirical distributions (ECDF) attached to the two datasets. It works both with categorical and numerical features, and returns […]

Data Sets Featured Posts Generative AI Machine Learning Python Synthetic Data

How to Fix a Failing Generative Adversarial Network

In this article, I explore different front-end strategies to improve a generative adversarial network (GAN) that leads to poor synthetization, in the context of tabular data generation. It is well known that tabular data is a lot more challenging than images, when using deep neural networks for synthetization purposes. An algorithm may work very well […]

Data Sets Explainable AI Featured Posts Generative AI Synthetic Data Time Series

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 […]

Data Sets Experimental Math Featured Posts Generative AI Synthetic Data Time Series

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 […]

Data Sets Featured Posts Synthetic Data

Generative AI: Synthetic Data Vendor Comparison and Benchmarking Best Practices

The goal of data synthetization is to produce artificial data that mimics the patterns and features present in existing, real data. Many generation methods and evaluation techniques are available, depending on purposes, the type of data, and the application field. Everyone is familiar with synthetic images in the context of computer vision, or synthetic text […]

Courses Data Sets Deep Learning Explainable AI Featured Posts

Massively Speed-Up your Learning Algorithm, with Stochastic Thinning

Dramatically Speed-Up your Learning Algorithm, with Stochastic Thinning. Includes use case, Python code, regression and neural network illustrations.

Data Sets Featured Posts Machine Learning

Feature Clustering: A Simple Solution to Many Machine Learning Problems

Feature clustering is an unsupervised machine learning technique to separate the features of a dataset into homogeneous groups. In short, it is a clustering procedure, but performed on the features rather than on the observations. Such techniques often rely on a similarity metric, measuring how close two features are to each other. In this article, […]

Books Data Sets Deep Learning Explainable AI Featured Posts Machine Learning Synthetic Data

Data Synthetization: enhanced GANs vs Copulas

Using case studies, I compare generative adversarial networks (GANs) with copulas to synthesize tabular data. I discuss back-end and front-end improvements to help GANs better replicate the correlation structure present in the real data. Likewise, I discuss methods to further improve copulas, including transforms, the use of separate copulas for each population segment, and parametric […]

Books Data Sets Explainable AI Featured Posts Machine Learning Synthetic Data Visualization

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 […]

Data Sets Featured Posts Machine Learning Synthetic Data Time Series Visualization

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 […]

	Vincent Granville on Math for Machine Learning: 14…
	Francesco Pedulla' on Math for Machine Learning: 14…
	Vincent Granville on Fuzzy Regression: A Generic, M…
	Capri Granville on Computer Vision: Shape Classif…
	Vincent Granville on Amazing Neural Network Video D…