Machine Learning For Front-End Developers With Tensorflow.js

Machine learning often feels like it belongs to the realm of data scientists and Python developers. However, over the past couple of years, open-source frameworks have been created to make it more accessible in different programming languages, including JavaScript. In this article, we will use Tensorflow.js to explore the different possibilities of using machine learning in the browser through a few example projects.

What Is Machine Learning?

Before we start diving into some code, let’s talk briefly about what machine learning is as well as some core concepts and terminology.


A common definition is that it is the ability for computers to learn from data without being explicitly programmed.

If we compare it to traditional programming, it means that we let computers identify patterns in data and generate predictions without us having to tell it exactly what to look for.

Let’s take the example of fraud detection. There is no set criteria to know what makes a transaction fraudulent or not; frauds can be executed in any country, on any account, targeting any customer, at any time, and so on. It would be pretty much impossible to track all of this manually.

However, using previous data around fraudulent expenses gathered over the years, we can train a machine-learning algorithm to understand patterns in this data to generate a model that can be given any new transaction and predict the probability of it being fraud or not, without telling it exactly what to look for.

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