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coursera-ml-007-exercises
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61 Commits (4bc9a2b246e1a84e87e176db8aa63296f028f2b2)
 

Author SHA1 Message Date
neingeist 4bc9a2b246 Estimate Gaussian
neingeist 33e8cbac01 Add exercise 8
neingeist beb652a5be Recover data
neingeist 798f82ecc1 Project data
neingeist 2b98bd80f0 Implement PCA
neingeist 5f3f65c69c Random initialization
neingeist 6c51a29ca2 Compute centroid means (vectorized)
neingeist 39b09f144a Compute centroid means (unvectorized)
neingeist f8c0087ff3 Find closest centroids
neingeist 229023b69c Add exercise 7
neingeist 348d6325cb Email feature extraction
neingeist f0d4b4d208 Preprocess email
neingeist 203cbc997c Implement grid search and determine best parameters for C and sigma
neingeist e67166bc8e Implement Gaussian kernel
neingeist 7ab47a4d35 Add exercise 6
neingeist 2ab445f9a8 Compute the test set error
neingeist 78830aaea7 Validation curve function
neingeist 3751214442 Use lambda=1 for regularizing the polynomial fit
neingeist 717ea8c788 Polynomial feature mapping
neingeist 1cc58802eb Learning curve function
neingeist 90f2928cee Move .gitignore to top-level directory
neingeist 2d6da3e3d4 Regularized linear regression gradient
neingeist 6530916642 Regularized linear regression cost function
neingeist d93d111106 Add programming exercise 5
neingeist eccdcc0d81 Regularized NN gradient
neingeist bdecab8cf8 Implement back propagation
neingeist 052f0625c3 Random initialization
neingeist 863f1d7157 Compute the sigmoid gradient
neingeist 395c5676dc Add regularization to the cost function
neingeist f2154a8cc1 Compute cost function for the neural network
neingeist be6f3cbdef Move PDFs in top directory
neingeist a17f47e396 Add programming exercise 4
neingeist 073fbf0204 Add neural network prediction function
neingeist 3bf3d9fdc3 Add prediction function for one-vs-all classification
neingeist cf0d25440c Train num_labels one-vs-all logistic regression classifiers
neingeist 9117809537 Vectorized regularized logistic regression, again
neingeist 326a924044 Add exercise 3
neingeist f9243ef593 Simplify regularization term
neingeist 9e9b9990bb Compute the gradient for regularized logistic regression
neingeist f391ac661e Add cost function for regularized logistic regression
neingeist 224a17e4d3 Plot negative samples in red
neingeist c0b4d95f75 Predict
neingeist 31c4ac1967 Compute the gradient for logistic regression
neingeist 8c100a3f49 Compute the cost function for logistic regression
neingeist b863a3863e .gitignore ml_login_data.mat
neingeist efe94282b4 Compute the sigmoid function
neingeist d52fa95328 Plot the data
neingeist 580e52ddc5 Initial commit of ex2
neingeist ba377e29ba Linear regressing using the normal equation
neingeist ad9ab582de Gradient descent for multiple features