A guide for using the Wavelet Transform in Machine Learning

Posted on 51 CommentsPosted in Classification, convolutional neural networks, Machine Learning, recurrent neural networks, scikit-learn, Stochastic signal analysis, tensorflow, Uncategorized

1. Introduction In a previous blog-post we have seen how we can use Signal Processing techniques for the classification of time-series and signals. A very short summary of that post is: We can use the Fourier Transform to  transform a signal from its time-domain to its frequency domain. The peaks in the frequency spectrum indicate […]

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Using Convolutional Neural Networks to detect features in satellite images

Posted on 19 CommentsPosted in convolutional neural networks, tensorflow

1. Introduction In the previous blog post we have seen how to build Convolutional Neural Networks (CNN) in Tensorflow, by building various CNN architectures (like LeNet5, AlexNet, VGGNet-16) from scratch and training them on the MNIST, CIFAR-10 and Oxflower17 datasets. It starts to get interesting when you start thinking about the practical applications of CNN […]

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Building Convolutional Neural Networks with Tensorflow

Posted on 4 CommentsPosted in convolutional neural networks, deep learning, tensorflow

1. Introduction In the past I have mostly written about ‘classical’ Machine Learning, like Naive Bayes classification, Logistic Regression, and the Perceptron algorithm. In the past year I have also worked with Deep Learning techniques, and I would like to share with you how to make and train a Convolutional Neural Network from scratch, using tensorflow. […]

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