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33 Commits (395c5676dc6a0e6cda868ad96f053d2a769e3090)
 

Author SHA1 Message Date
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
neingeist 3dc8897634 Compute cost for multiple variables
neingeist e38033c00d Clean up whitespace
neingeist 8559c243c5 Normalize features
neingeist 613220bb3e Clean up whitespace
neingeist 38064db8b3 Print out the cost function J
neingeist 2bf076c2fc Gradient descent for one variable
neingeist 514431e135 .gitignore login data
neingeist 14c85aa85c Compute Cost (for one variable)
neingeist bc0eb3519f Plot the data
neingeist 136815f0b7 Warmup exercise
neingeist 79825e97f4 import exercise 1: IV. Linear Regression with Multiple Variables (Week 2)