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 … [Read more…]
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.
I re-wrote the Poisson Blending code using C++ and OpenCV. About the Algorithm, see my Previous Poisson Blending post. This time, I just used the most stupid way, just solving the Poisson Equation. You can improve it by using advanced methods. About solving discrete Poisson Equation using Jacobi, SOR, Conjugate Gradients, and FFT, read THIS. In … [Read more…]
This is the same algorithm with the previous SOFTMAX REGRESSION post. Because I’m going to try to build deeper neural networks for images, so as a review of OpenCV programming, I rewrote the Softmax regression code using OpenCV mat, instead of Armadillo. I used Matlab, Octave, Armadillo a lot these days, it is kind of … [Read more…]
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 … [Read more…]
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 … [Read more…]
WHAT IS SOFTMAX Softmax regression always as one module in a deep learning network, and most likely to be the last module, the output module. What is it? It is a generalized version of logistic regression. Just like logistic regression, it belongs to supervised learning, and the superiority is, the class label y can be more than … [Read more…]
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 … [Read more…]
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.
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.