Developing MLP Artificial Neural Networks from scratch in C: An Introduction to scratchANN

prerequisite: basics of C programming and ANNs
In this video covers:
1. introduction to scratchANN. scratchANN is a lightweight artificial neural network (ANN) library written in C, designed for educational and experimental purposes. It offers a simple yet powerful framework for building and training multilayer perceptron models. The library provides essential features to define and train ANNs, allowing users to customize the number of layers, neurons, and activation functions.
2. A detailed case study demonstrating the creation of an MLP model using scratchANN and training it on the Energy Efficiency dataset. The results are compared against a TensorFlow-based model implemented in Python, highlighting performance, accuracy, and key differences between the two approaches.
If you are not familiar with C programming and ANNs you can start with "C Programming for Noobs". Download from:
github.com/ped...
Download scratchANN:
github.com/ped...

[@aleekitstore1448]

Good Job Thats the Best AI video and tutorial i ve ever Seen You Remind Me of of David J.Mallan

[@pedrampasandide8946]

Thanks for watching! Glad you found it helpful

[@daleanfer7449]

just looking for content like this,hoping to have a video about tensor backprop in c

[@pedrampasandide8946]

trainModel() in scratchANN has multiple sub functions and one of them is Backward_Pass(). In this function, right before updating the weights and bias, the same concept of backpropagation with SGD algorithm is implemented. However, if other optimizations is needed, for example Adam or a global optimizations algorithm, some changes are required to be done within Backward_Pass(). Maybe in the future I discuss this topic in details or add more optimization algorithms to scratchANN. You can start with my lecture notes, C Programming for Noobs, free to download on my GitHub. There is a section discussing backprop formulation.

[@DesiderioElke]

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[@pedrampasandide8946]

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