Using Convolutional Neural Networks to detect features in satellite images

Posted on 1 CommentPosted 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 2 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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Regression, Logistic Regression and Maximum Entropy part 2 (code + examples)

Posted on 9 CommentsPosted in Classification, Sentiment Analytics

update: The Python code for Logistic Regression can be forked/cloned from my Git repository. It is also available on PyPi. The relevant information in the blog-posts about Linear and Logistic Regression are also available as a Jupyter Notebook on my Git repository.   Introduction In the previous blog we have seen the theory and mathematics behind the […]

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Hello world!

Posted on Leave a commentPosted in Uncategorized

“I have no doubt that in reality the future will be vastly more surprising than anything I can imagine. Now my own suspicion is that the Universe is not only stranger than we imagine, but queerer than we can imagine.” like most geeks, I am interested in future technologies and frequently read up on it. I find […]

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