Machine learning is easily one of the biggest buzzwords in tech right now. Over the past three years Google searches for “machine learning” have increased by over 350%. But understanding machine learning can be difficult — you either use pre-built packages that act like ‘black boxes’ where you pass in data and magic comes out the other end, or you have to deal with high level maths and linear algebra.
This tutorial is designed to introduce you to the fundamental concepts of machine learning — you’ll build your very first model from scratch to make predictions, while understanding exactly how your model works.
This tutorial is based on our Dataquest Machine Learning Fundamentals course, which is part of our Data Science Learning Path. The course goes into a lot more detail, and allows you to follow along writing code to learn by doing.
To start though, let’s explore what machine learning actually is.
What is machine learning?
Machine learning is the practice of building systems, known as models, that can be trained using data to find patterns which can then be used to make predictions on new data.
An important distinction is that a machine learning...
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