I implemented a basic MLP that supports different activation and loss functions. It was trained via mini-batch gradient descent. I wrote it from scratch, using no external libraries except Eigen (for linear algebra).

I learned how a Neural Network learns (all the math) -- how the forward pass works, and how learning via backpropagation works. How to convert all that math into code.

I’ll write a blog soon explaining how MLPs work in plain English. My dream is to get into MIT/Harvard one day by following my passion for understanding and building intelligent systems. Ive attached link to my GitHub repo. Feedback is much appreciated!!