Optimisation

Embedding Models Explained, How To Use Them & 10 Tools/Frameworks

What Are Embedding Models? At their core, embedding models are tools that convert complex data—such as words, sentences, images, or…

17 hours ago

Vector Embeddings Made Simple & How To Tutorial In Python

What Are Vector Embeddings? Imagine trying to explain to a computer that the words "cat" and "dog" are more similar…

4 days ago

Monte Carlo Tree Search Explained & How To Implement [With Code]

What is Monte Carlo Tree Search? Monte Carlo Tree Search (MCTS) is a decision-making algorithm that helps an agent figure…

2 weeks ago

Dynamic Programming Explained & How To Tutorial In Python

What is Dynamic Programming? Dynamic Programming (DP) is a powerful algorithmic technique used to solve complex problems by breaking them…

4 weeks ago

Temporal Difference Learning Made Simple With Example & Alternatives

What is Temporal Difference Learning? Temporal Difference (TD) Learning is a core idea in reinforcement learning (RL), where an agent…

1 month ago

Understanding Interdependent Variables: The Hidden Web Of Cause And Effect

Have you ever wondered why raising interest rates slows down inflation, or why cutting down forests affects rainfall patterns? These…

2 months ago

Deep Deterministic Policy Gradient Made Simple & How To Tutorial In Python

Introduction Reinforcement Learning (RL) has seen explosive growth in recent years, powering breakthroughs in robotics, game playing, and autonomous control.…

3 months ago

Viterbi Algorithm Made Simple [How To & Worked-Out Examples]

Introduction Imagine trying to understand what someone said over a noisy phone call or deciphering a DNA sequence from partial…

4 months ago

Structured Prediction In Machine Learning: What Is It & How To Do It

What is Structured Prediction? In traditional machine learning tasks like classification or regression a model predicts a single label or…

4 months ago

Policy Gradient [Reinforcement Learning] Made Simple In An Elaborate Guide

Introduction Reinforcement Learning (RL) is a powerful framework that enables agents to learn optimal behaviours through interaction with an environment.…

4 months ago