Writing
Short notes on backend engineering, tools, and whatever I'm working through at the moment. 8 posts so far.
Read in order
Series
- Part of Neural Network From Scratch Using Numpy only
Oct 14, 2026From One Neuron to a Network: A Multilayer Forward Pass With NumPy
Build a small neural network from layers of neurons, trace how weights and biases transform an input, and implement the forward pass using only NumPy.
neural networksnumpypythonforward propagationbeginners8 min - Part of Neural Network From Scratch Using Numpy onlyOct 14, 2026
Training a Multilayer Neural Network With NumPy: Backpropagation From Scratch
Extend a NumPy forward pass into a trainable multilayer network. Generate synthetic targets, derive hidden-layer gradients, and use backpropagation with stochastic gradient descent.
neural networksbackpropagationgradient descentnumpypythonbeginners10 min - Part of Neural Network From Scratch Using Numpy onlyOct 05, 2026
A Single Neuron From Scratch With NumPy: Weights, Bias, and Activation Functions
The first post in Neural Network From Scratch Using Numpy Only. Build one neuron, walk through the forward pass by hand, and compare step, sigmoid, and ReLU activations.
neural networksnumpypythonmachine learningbeginners12 min - Part of Neural Network From Scratch Using Numpy onlyOct 05, 2026
Teaching a Single Neuron to Learn: Backpropagation and Gradient Descent in NumPy
Part two of Neural Network From Scratch Using Numpy Only. Add a loss function, derive gradients with the chain rule, and watch a neuron with random weights learn the right ones.
neural networksbackpropagationgradient descentnumpypythonbeginners16 min - Part of Neural Network From Scratch Using Numpy onlyOct 05, 2026
Why One Neuron Isn't Enough: The XOR Problem and the Case for Hidden Layers
Part three of Neural Network From Scratch Using Numpy Only. See why a single neuron can only draw a straight line, watch it fail on XOR, and learn why hidden layers and non-linear activations change everything.
neural networksxor problemhidden layersnon-linearitynumpypythonbeginners14 min - Part of Machine Learning FundamentalsSep 24, 2026
Training, Validation, and Test Splits: Why They Matter in Machine Learning
A detailed guide to splitting machine learning data, the problem validation sets solve, how leakage creates false confidence, and how to evaluate models honestly.
machine learningmodel evaluationdata sciencebeginners15 min - Sep 23, 2026
Types of Machine Learning: Supervised, Unsupervised, and More
A detailed guide to supervised, unsupervised, semi-supervised, self-supervised, and reinforcement learning, including algorithms, examples, and how to choose an approach.
machine learningalgorithmsdata sciencebeginners13 min - Sep 22, 2026
What is Machine Learning? Traditional Programming vs Machine Learning
A clear, practical introduction to machine learning, how models learn from data, and how this approach differs from traditional rule-based programming.
machine learningartificial intelligenceprogrammingbeginners9 min
