Category Archives: Machine Learning

“Researchers Make Computer Chess Programs More Human” on the Pure AI Web Site

I contributed to an article titled “Researchers Make Computer Chess Programs More Human” on the September 2022 edition of the Pure AI web site. See https://pureai.com/articles/2022/09/06/more-human-chess-programs.aspx. In some machine learning scenarios, it’s useful to make a prediction system that is … Continue reading

Posted in Machine Learning | Leave a comment

The Maia Computer Chess Program

I came across an interesting research project named Maia. Maia is a computer chess program that was designed to play more like a human than conventional chess programs. See https://www.microsoft.com/en-us/research/project/project-maia/. There is a long and fascinating history of chess, computer … Continue reading

Posted in Machine Learning | Leave a comment

ANOVA Using C# in Visual Studio Magazine

I wrote an article titled “ANOVA Using C#” in the August 2022 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2022/08/17/anova-csharp.aspx. Analysis of variance (ANOVA) is a classical statistics technique that’s used to infer if the means (averages) of three or … Continue reading

Posted in Machine Learning | Leave a comment

Researchers Demonstrate Transformer Architecture-Based Anomaly Detection for Cybersecurity on the Pure AI Web Site

I contributed to an article titled “Researchers Demonstrate Transformer Architecture-Based Anomaly Detection for Cybersecurity” on the Pure AI web site. See https://pureai.com/articles/2022/08/02/ta-anomaly-detection.aspx. Researchers at Microsoft have demonstrated a new technique for anomaly detection. The technique is based on deep neural … Continue reading

Posted in Machine Learning | Leave a comment

The Difference Between Encoding, Embedding, and Latent Representation — in My World

Bottom line: In the machine learning projects I work on, an encoding converts categorical data to numeric data (example: one-hot encoding where “red” = [0 1 0 0]), an embedding converts an integer word ID to a vector (ex: “the” … Continue reading

Posted in Machine Learning | Leave a comment

Yes, TensorFlow is Dead

July 2022: the TensorFlow neural network code library is dead. OK, that statement is somewhat of a provocative exaggeration but bear with me. It’s impossible to get hard data about the usage of TensorFlow (and Keras) relative to the other … Continue reading

Posted in Keras, Machine Learning, PyTorch | 2 Comments

DARPA Funds the Adversarial Robustness Toolbox (ART) Library for ML Security on the Pure AI Web Site

I contributed to an article titled “DARPA Funds the Adversarial Robustness Toolbox (ART) Library for ML Security” on the Pure AI web site. See https://pureai.com/articles/2022/07/05/darpa-art.aspx. The Adversarial Robustness Toolbox (ART) library is an open source collection of functions for machine … Continue reading

Posted in Machine Learning | Leave a comment

A First Look at Deep Neural Perceiver Models

I ran across an interesting research paper titled “Perceiver: General Perception with Iterative Attention”, by A. Jaegle et al. (2021). A Perceiver model is a general Transformer. There are two key ideas. First, the architecture of a Transformer model has … Continue reading

Posted in Machine Learning | Leave a comment

Researchers Generate Realistic Images from Text on the Pure AI Web Site

I contributed to an article titled “Researchers Generate Realistic Images from Text” on the Pure AI web site. See https://pureai.com/articles/2022/06/01/images-from-text.aspx. The article describes how researchers at Google have demonstrated a new technique that generates photo-realistic images from arbitrary text. The … Continue reading

Posted in Machine Learning | Leave a comment

Probit Regression Using C# in Visual Studio Magazine

I wrote an article titled “Probit Regression Using C#” in the June 2022 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2022/06/01/probit-regression.aspx. Probit (“probability unit”) regression is a classical machine learning technique that can be used for binary classification — predicting … Continue reading

Posted in Machine Learning | Leave a comment