back to the devlog
ResearchResearch2025
Neural Network from Scratch
A ground-up neural network implementation in pure Python — no frameworks, just math. Covers neurons, layers, activation functions, and loss calculation.
focus
Deep understanding of neural network fundamentals by implementing every component from first principles.
milestones
01
Built forward-pass computation with dot products and layer objects
02
Implemented ReLU and Softmax activation functions from scratch
03
Coded categorical cross-entropy loss calculation
04
Demonstrated multi-input neuron and multi-layer architectures