What is machine learning? A beginner’s guide
Machine learning infers rules from examples. This guide covers its definition, its three ways of learning, how we check that it works, its limits and where it sits in European regulation.
Machine learning
Deep Learning vs Machine Learning: What’s the Difference?
Deep learning is a subfield of machine learning. We look at what separates the two, when each tends to suit, why deep learning took off in 2012, and where its limits lie.
The Most Common Machine Learning Algorithms, and When to Use Each One
A decision guide to choosing between linear models, logistic regression, decision trees, random forests, gradient boosting and neural networks on tabular data, with NumPy code and the limits of each approach.
How Neural Networks Work: A Step-by-Step Guide with Code
What changes inside a neural network when it “learns”: neurons, layers, the loss function, backpropagation and gradient descent, with a minimal NumPy version and the same loop in PyTorch.