Category Archives: PAW

Recap of the 2022 Machine Learning Week Conference

Posted on July 5, 2022 by jamesdmccaffrey

I presented a workshop titled “Deep Learning in Practice: A Hands-On Introduction” at the 2022 Machine Learning Week conference. The event ran June 19-24 and was in Las Vegas. Machine Learning Week is co-located with the Predictive Analytics World conference. … Continue reading →

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Installing Keras 2.8 on a MacBook Laptop

Posted on June 18, 2022 by jamesdmccaffrey

It had been several months since I used a MacOS machine for machine learning with Keras/TensorFlow so I decided to do some examples to make sure there were no significant breaking changes. I bought a refurbished MacBook Air from the … Continue reading →

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IMDB Sentiment Classification Using Keras 2.8 on Windows 11

Posted on June 9, 2022 by jamesdmccaffrey

One of my standard neural network examples is sentiment classification on the IMDB Movie Review dataset. The goal is to predict the sentiment (0 = negative, 1 = positive) of a natural language movie review such as, “The movie was … Continue reading →

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IMDB Sentiment Classification Using PyTorch 1.10 on Windows 11

Posted on June 6, 2022 by jamesdmccaffrey

One of my standard neural network examples is sentiment classification on the IMDB Movie Review dataset. The goal is to predict the sentiment (0 = negative, 1 = positive) of a natural language movie review such as, “The movie was … Continue reading →

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Installing PyTorch 1.10.0 on a MacBook Laptop

Posted on June 5, 2022 by jamesdmccaffrey

I most often use Windows OS machines but I sometimes use Mac and Linux machines too. It had been several months since I had used the PyTorch neural network library on a Mac machine so one weekend I figured I’d … Continue reading →

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MNIST Image Classification Using Keras 2.8 on Windows 11

Posted on May 27, 2022 by jamesdmccaffrey

One of my standard neural network examples is image classification on the MNIST dataset. The full MNIST (modified National Institure of Standards and Technology) dataset has 60,000 images for training and 10,000 images for testing. Each image is a 28 … Continue reading →

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MNIST Image Classification Using PyTorch 1.10 on Windows 11

Posted on May 26, 2022 by jamesdmccaffrey

One of my standard neural network examples is image classification on the MNIST dataset. The full MNIST (modified National Institute of Standards and Technology) dataset has 60,000 images for training and 10,000 images for testing. Each image is a 28 … Continue reading →

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Regression (Employee Income) Using Keras 2.8 on Windows 11

Posted on May 24, 2022 by jamesdmccaffrey

One of my standard neural network examples is to predict employee income from sex, age, city, and job-type. Predicting a single numeric value is usually called a regression problem. (Note: “logistic regression” predicts a single numeric probability value between 0.0 … Continue reading →

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Regression (Employee Income) Using PyTorch 1.10 on Windows 11

Posted on May 23, 2022 by jamesdmccaffrey

One of my standard neural network examples is to predict employee income from sex, age, city, and job-type. Predicting a single numeric value is usually called a regression problem. (Note: “logistic regression” predicts a single numeric probability value between 0.0 … Continue reading →

Posted in PAW, PyTorch | 1 Comment

Autoencoder Anomaly Detection Using Keras 2.8 on Windows 11

Posted on May 19, 2022 by jamesdmccaffrey

Every few months I revisit my standard neural network examples to make sure that changes in the underlying code libraries (PyTorch, Keras/TensorFlow) haven’t introduced a breaking change(s). One of my standard examples is autoencoder anomaly detection. The idea is to … Continue reading →

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