Category Archives: Machine Learning

PyTorch train() vs. eval() Mode

The bottom line of this post is: If you use dropout in PyTorch, then you must explicitly set your model into evaluation mode by calling the eval() function mode when computing model output values. Bear with me here, this is … Continue reading

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Matrices with JavaScript

Like many programmers, I have a love-hate relationship with the JavaScript language. I’m quite familiar with the language but I sometimes go long stretches of time where I don’t use it frequently. A few days ago, a book publisher contacted … Continue reading

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Anomaly Detection Using a Deep Neural Autoencoder

Anomaly detection is the process of finding unusual data items. One standard approach is to cluster the data and then look at clusters with very few items, or at items that are far away from their cluster mean/average. Unfortunately, in … Continue reading

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NFL 2018 Week 20 (Conference Championships) Predictions – Zoltar Barely Likes the Saints and the Patriots

Zoltar is my NFL prediction computer program. It uses a deep neural network and reinforcement learning. Here are Zoltar’s predictions for week #20 of the 2018 NFL season (third weekend of playoffs): Zoltar: saints by 4 dog = rams Vegas: … Continue reading

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I Give a Talk About Neural Regression Using PyTorch

I work at a large tech company. One of the things I do at work is present short (about an hour) talks on machine learning and artificial intelligence topics. A few days ago I gave a talk on performing regression … Continue reading

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The Differences Between Neural Multiclass Classification, Regression, and Binary Classification

There are three basic forms of neural networks: multiclass classification, regression, and binary classification. There are also many kinds of more sophisticated neural problems, such as image classification using a CNN, text analysis using an LSTM, and so on. In … Continue reading

Posted in Machine Learning

Self-Organizing Maps Using C#

I wrote an article titled “Self-Organizing Maps Using C#” in the January 2019 issue of Microsoft MSDN Magazine. See https://msdn.microsoft.com/en-us/magazine/mt848708. It’s very difficult to explain exactly what a self-organizing map (SOM) is. One explanation is that a SOM is a … Continue reading

Posted in Machine Learning