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Zero-Shot vs One-Shot vs Few-Shot Prompting

Prompt Engineering

Zero-Shot vs One-Shot vs Few-Shot Prompting

Zero-shot, one-shot, and few-shot prompting explained in simple English. When to use each, and why extra examples can bias the answer on smaller models.

Sep 13, 2026·12 min read

Introduction to Computer Vision: How Machines Learn to See

Computer Vision

Introduction to Computer Vision: How Machines Learn to See

Computer vision is the field of making machines understand the world through images and videos, just like we humans do with our eyes and brain. Whether it’s your phone unlocking when it sees your face or a…

May 22, 2025·5 min read

Multi-Layer Perceptrons Explained

Deep Learning

Multi-Layer Perceptrons Explained

In this article, I will explain the intuitive workings behind Multi-Layer Perceptrons (MLPs), a critical concept in advanced neural networks. You’ll learn about the following:

Jan 3, 2025·7 min read

MLP Notation and Trainable Parameters

Deep Learning

MLP Notation and Trainable Parameters

In this short article, I’ll explain the standard notation used in Multilayer Perceptrons (MLPs), which is crucial for anyone starting with neural networks. You’ll learn how to:

Dec 26, 2024·5 min read

Introduction to Perceptron: The First Step in Neural Networks

Deep Learning

Introduction to Perceptron: The First Step in Neural Networks

The Perceptron is a fundamental concept in neural network theory, representing the simplest form of a neural network. Developed in 1958 by Frank Rosenblatt, it is a type of artificial neuron that uses binary…

Sep 3, 2024·8 min read

The Limitations of Perceptron: Why it Struggles with XOR

Deep Learning

The Limitations of Perceptron: Why it Struggles with XOR

Perceptrons, introduced by Frank Rosenblatt in the late 1950s, represent one of the simplest forms of artificial neural networks. They are binary classifiers that use a linear decision boundary to classify input data…

Sep 3, 2024·4 min read