As previously mentioned, machine learning is part of data science and therefore not strictly confined to a specific role; you can be a data scientist working with machine learning and AI technologies.

About This module is essential to providing the required knowledge and understanding of the importance of data science and machine learning techniques, within the context of real-world examples. Data ...

Before data scientists can run machine learning models to tease out insights, they’re first going to need to transform the data—reformatting it or perhaps correcting it—so it’s in a ...

Garbage In, Garbage Out Both artificial intelligence and machine learning business use cases need vast amounts of data to train the algorithms. For the most accurate results – the ones that you want ...

Using data based on the fraudster’s device, email, IP, phone, transaction and behavioural user information, machine learning can determine a fraudster’s true location, and look for high-risk ...

In order to train machine learning capabilities you need to have access to data – lots of it, and of sufficiently high quality in order to achieve the best results.

It’s axiomatic to say that data is the new oil of the digital economy, but this is especially true in fields like machine learning. Contemporary AI systems generally learn by example, so if you ...