Neural Networks Learning
Machine Learning Notes(8)Neural Networks Representation
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Neural Networks Model
 A single neuron model: logistic unit
 Takes 3+1 inputs(the extra input called bias is just like $\theta_0$ in logistic regression, not shown in picture).
 Both input and output could be represented as vectors, in which each unit has its own parameters $\theta$
 All the units in the same layer take the same input $\mathbf{x}$, as the pic shows.
 Each unit has only one output: $sigmoid(\theta^T x)$. Of course there’re other choices for sigmoid function.
 Neural Networks
 A neural network consists of an input Layer, an output layer and hidden layers.
 In the model above, layer 1 is input layer, 2 is hidden layer and 3 is the output layer.
Machine Learning Notes(5)Programming Exercise 1
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Programming Exercise 1: Gradient Descent for Linear regression
Machine Learning Notes(4)Octave abc
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Too lazy to explain some of the commands…orz
Machine Learning Notes(3)Multivariate Linear Regression
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Multivariate Linear Regression
Machine Learning Notes(2)A Linear Regression Example
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This is my notes for the open course Machine Learning from coursera.
Machine Learning Notes(1)Supervised and Unsupervised Learning
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This is my notes for the open course Machine Learning from coursera.