Tag Archives: UFLDL

A Simple Deep Network

During this spring break, I worked on building a simple deep network, which has two parts, sparse autoencoder and softmax regression. The method is exactly the same as the “Building Deep Networks for Classification” part in UFLDL tutorial. For better understanding it, I re-implemented it using C++ and OpenCV.  GENERAL OUTLINE Read dataset (including training data […]

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[UFLDL Exercise] Convolution and Pooling

I’m learning Prof. Andrew Ng’s Unsupervised Feature Learning and Deep Learning tutorial, This is the 8th exercise, which is a simple ConvNet with Pooling process. I’ll not go through the detail of the material. More details about this exercise can be found HERE. I’ll try to implement it using C++ and OpenCV if I have time next week.

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[UFLDL Exercise] Implement deep networks for digit classification

I’m learning Prof. Andrew Ng’s Unsupervised Feature Learning and Deep Learning tutorial, This is the 6th exercise, which is a combination of Sparse Autoencoder and Softmax regression algorithm, and fine-tuning algorithm. It builds a 2-hidden layers sparse autoencoder net and one layer Softmax regression, we first train this network layer by layer, from left to right, then […]

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[UFLDL Exercise] Self-Taught Learning

I’m learning Prof. Andrew Ng’s Unsupervised Feature Learning and Deep Learning tutorial, This is the 5th exercise, which is a combination of Sparse Autoencoder and Softmax regression algorithm. It uses the features trained by sparse autoencoder as training input of Softmax regression, and builds a classifier which have more accuracy than regular softmax regression. I’ll not go through […]

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[UFLDL Exercise] Softmax Regression

I’m learning Prof. Andrew Ng’s Unsupervised Feature Learning and Deep Learning tutorial, This is the 4th exercise, which is using Softmax regression to build a classifier and classify MNIST handwritten digits. Just like my other UFLDL exercise posts, I’ll not go through the detail of the material. More details about this exercise can be found HERE. I’ll re-implement Softmax […]

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[UFLDL Exercise] PCA and Whitening

I’m learning Prof. Andrew Ng’s Unsupervised Feature Learning and Deep Learning tutorial, This is part 2 of the 3rd exercise, which is use PCA algorithm in a natural image dataset. Just like my other UFLDL exercise posts, I’ll not go through the detail of the material. More details about this exercise can be found HERE.

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[UFLDL Exercise] PCA in 2D

I’m learning Prof. Andrew Ng’s Unsupervised Feature Learning and Deep Learning tutorial, This is part 1 of the 3rd exercise, which is use PCA algorithm in a simple 2D dataset. Just like my other UFLDL exercise posts, I’ll not go through the detail of the material. More details about this exercise can be found HERE.

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[UFLDL Exercise] Sparse Autoencoder

I’m learning Prof. Andrew Ng’s Unsupervised Feature Learning and Deep Learning tutorial, I finished the first exercise, the tutorial is very professional and easy to learn. I don’t think I need to go through the detail of what Sparse Autoencoder is, I’ll put my code of the exercise here, if you have any question about it, feel […]

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