Category Archives: Machine Learning

I Give a Workshop on Introduction to Neural Networks using CNTK v2

I recently gave a one-hour workshop on neural networks using CNTK v2. CNTK is an open source code library that can be used to create neural networks. Getting started with CNTK can be a bit difficult. For my example, I … Continue reading

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Still Yet Another Look at LSTM Time Series Regression

One of my personality weaknesses is that when a technical problem gets stuck in my head, I’m incapable of letting it go. Literally. I can think of several problems that stuck in my brain for several years until I finally … Continue reading

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Sentiment Analysis using an LSTM Neural Network

I found an excellent example of building a sentiment analysis prediction model using an LSTM neural network with Keras. The problem is to take the text of several thousand movie reviews from the IMDB Web site that have been marked … Continue reading

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Decision Tree Classification

I’m not a big fan of decision tree classification. Although decision trees have a couple of advantages over neural network classifiers (simplicity, somewhat able to interpret), decision trees rarely work as well as neural networks, at least on the types … Continue reading

Posted in Machine Learning

Why You Shouldn’t Apply Softmax Twice to a Neural Network

I was presenting a talk about the Microsoft CNTK neural network library recently. CNTK has a quirk that isn’t explained anywhere in the documentation. Briefly, unless you’re careful, when you train a CNTK neural network classifier, you will apply softmax … Continue reading

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Using a Neural Network Created by CNTK or TensorFlow in a C# Program

Whenever I give a technical talk on neural networks with the CNTK or TensorFlow or Keras libraries, I usually get a question like, “OK, I understand how to create and train a neural network using CNTK/TF/Keras using Python. But my … Continue reading

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Earth Mover Distance Wasserstein Metric Example Calculation

The Earth Mover Distance (EMD) is the distance between two mathematical distributions. EMD is also called the Wasserstein metric. Here’s an example of how EMD is calculated. Suppose you have a distribution called “holes” with 13 values where each value … Continue reading

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