We are currently developing our own machine learning platform with an emphasis on text mining and we are looking for a reproducible methodology to implement backpropagation.
Where can I find a "manual" to implement it?
I'd recommend, for easier implementation, you outline the problem you need to solve, use a flowchart if possible or any diagramming tool to draw the flow you wish to attain, afterwards you put down the pseudocode of the implementation.. By so doing, you'll have a firm understanding of the final implementation when writing the program on any language.. I believe the routine can be done with any programming language you're very familiar with and not just learning a new one..
Note: The final implementation must follow the back propagation principle for artificial neural network...
Thanks.
For further reading: http://ieeexplore.ieee.org/abstract/document/298623/
Kindly have a look at the following URL to learn implementation details of back-propagation routine in PYTHON from scratch:
https://machinelearningmastery.com/implement-backpropagation-algorithm-scratch-python/
Thanks
Hello Ruediger,
I am sharing a PDF with this answer. This is the best way to implement backpropagation in a vectorized manner. Make sure you know how to use inbuilt libraries for optimization algorithms.
The best
Hi Nikhil, thanx for the information and the pdf file. That is very helpful.
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