← All articles

Machine Learning

Machine Learning explainers and exam-revision guides from Full Marks Press.

AllAI Ethics and Responsible AIComputer VisionDeep Learning and Neural NetworksGenerative AI and NLPMachine LearningMaths, Programming and MLOpsRevision and Lecturer Resources
How to explain gradient descent in a university exam
Machine Learning

How to explain gradient descent in a university exam

Gradient descent is an iterative optimisation algorithm used in machine learning to find the local minimum of a differentiable cost function. It works by cal

How to write a standout data science project proposal for your master's degree
Machine Learning

How to write a standout data science project proposal for your master's degree

A standout data science project proposal clearly defines a specific research problem, details the exact dataset you will use, and outlines the machine learni

K-means clustering explained: worked examples for exam revision
Machine Learning

K-means clustering explained: worked examples for exam revision

K-means clustering is an unsupervised machine learning algorithm that groups unlabelled data into a pre-defined number of distinct clusters, represented by t

Overfitting vs underfitting: how to secure top marks in ML assignments
Machine Learning

Overfitting vs underfitting: how to secure top marks in ML assignments

Overfitting occurs when a machine learning model memorises the training data, including its random noise, resulting in poor predictions on unseen data. Under

What are the best ways to revise decision trees for undergraduate exams?
Machine Learning

What are the best ways to revise decision trees for undergraduate exams?

The best way to revise decision trees for undergraduate exams is to master the mathematical formulas for splitting criteria, specifically Entropy and Gini im

What is the difference between supervised and unsupervised learning?
Machine Learning

What is the difference between supervised and unsupervised learning?

The main difference between supervised and unsupervised learning lies in the data used to train the algorithms. Supervised learning uses labelled datasets wh

Why do ensemble methods perform better? An exam-focused breakdown
Machine Learning

Why do ensemble methods perform better? An exam-focused breakdown

Ensemble methods perform better because they combine multiple diverse base models to reduce the overall predictive error rate. By aggregating individual pred

Frequently asked questions

What does the Machine Learning category cover?

It collects exam-focused Machine Learning explainers and revision guides from Full Marks Press, written for university students.

Who writes these Machine Learning guides?

Every article is written by Sotiris Spyrou, published by Full Marks Press.

Are these guides free?

Yes. Every article is free to read, and you can request a free review copy of the related guide at https://fullmarkspress.com/free.