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notes's Introduction

notes

Contains Example Programs and Notebooks for courses offered by A. Taylan Cemgil at Bogazici University, Department of Computer Engineering

. CMPE 250 Data Structures

. CMPE 547, Bayesian Statistics and Machine Learning

. CMPE 548, Monte Carlo Methods,

. CMPE 58R, Statistical Data Analysis,

. CMPE 482, Numerical Linear Algebra and Its Applications,

. CMPE 462, Machine Learning,

. SWE 546, Data Mining,

. SWE 582, Machine Learning for Data Analytics,

. FE 587, Computer Programming for Finance

. FE 588, Python Programming for Finance

Ali Taylan Cemgil

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notes's Issues

Matrix dimensions do not match

In notes/MultiLayerPerceptron.ipynb, there is a dimensional conflict in this function:

def mlp_fun(x, Weight, Bias, Func):
    f = Variable(x, requires_grad=False)
    NumOfLayers = len(Weight)
    for i in range(NumOfLayers):
        f = Func[i](torch.matmul(Weight[i], f) + Bias[i])
    return f

I have printed all steps for a 1,2,1 sized network, below are the results:
image

While the result of torch.matmul(Weight[0], x) is a 1x2 matrix, Bias[0] is a 2x1 vector and their summation is a 2x2 matrix.

This leads to a dimensional conflict in f results.

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