# MATLAB Machine Learning Book is Now Available

Apress just published our new book, “MATLAB Machine Learning”

written by Michael Paluszek and Stephanie Thomas. The book covers a wide variety of topics related to machine learning including neural nets and decision trees. It also includes topics from automatic control including Kalman Filters and adaptive control. The book has many examples including autonomous driving, number identification and adaptive control of aircraft.

Full source code is available. For more information go to MATLAB Machine Learning.

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Michael Paluszek is President of Princeton Satellite Systems. He graduated from MIT with a degree in electrical engineering in 1976 and followed that with an Engineer's degree in Aeronautics and Astronautics from MIT in 1979. He worked at MIT for a year as a research engineer then worked at Draper Laboratory for 6 years on GN&C for human space missions. He worked at GE Astro Space from 1986 to 1992 on a variety of satellite projects including GPS IIR, Inmarsat 3 and Mars Observer. In 1992 he founded Princeton Satellite Systems.

## 8 thoughts on “MATLAB Machine Learning Book is Now Available”

• Dear Mahmoud:

I sent you an email with updated code. I didn’t change anything (except a path to cats1024) and it works fine.

Mike

1. Hi,
I am reading the book and going through the source code.
For chapter 7 I can see that at the end of the chapter there are listed a number of source code files that I cannot find on the project github.

Best,
Razvan

• Thanks for the feedback! What result did you get?

• the m-file convolutionalNN has an order r=softmax(q) , to get the value of r.
But when run the m-file TestNN , get this error

Undefined function ‘exp’ for input arguments of type ‘uint8’.

Error in Softmax (line 35)
den = sum(exp(q));

Error in ConvolutionalNN>NeuralNet (line 64)
r = Softmax( q );

Error in ConvolutionalNN>Testing (line 45)
[d, r] = NeuralNet( d, t );

Error in ConvolutionalNN (line 34)
r = Testing( d, t );

Error in TestNN (line 19)
[d, r] = ConvolutionalNN( ‘test’, d, t );

• Thanks! I’ll look into you and update the code. What version of MATLAB are you using?

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