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Helpful math for machine learning

Tristan
・1 min read

Introduction

  • This series is going to be my attempt to build a very basic neural network in C++ from scratch. All the information from this series can be found in the book, C++ Neural Networks and Fuzzy Logic by Valluru B. Rao.

Helpful math

  • On a more theoretical level of machine learning, according to the university of Toronto's machine learning and data mining class, found HERE , there are 4 sections of math that are helpful for machine learning.

1) Linear algebra: vector/matrix manipulations, properties

2) Calculus: partial derivatives/gradient

3) Probability : common distributions; Bayes Rule

4) Statistics : expectation, variance, covariance, median; maximum likelihood.

  • A broad overview of these sections of math can be found HERE

Conclusion

  • Thank you for taking the time out of your day to read this blog post of mine. If you have any questions or concerns please comment below or reach out to me on Twitter.

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