What is machine learning?
When it comes to Machine Learning (ML), everyone immediately thinks Artificial Intelligence and futuristic-type products like self-driving cars or Siri. So nowadays everybody is talking about it. Looking around only some really know how to do it. But everyone thinks everyone else is doing it so, everyone claims they’re doing it, too.
So what is Machine Learning really?
For a start Machine Learning (ML) and Artificial Intelligence (AI) are two separate entities that just so happen to complement each other and it’s only fair to say that Machine Learning – similar to Deep Learning – is a subset of Artificial Intelligence.
While artificial intelligence (AI) aims to harness certain aspects of the “thinking” mind, Machine Learning focuses on the ability of machines to receive a set of data and learn for themselves, changing algorithms as they learn more about the information they’re processing.
How do we apply Machine Learning to Digital Marketing?
Machine Learning enables organisations to leverage large datasets to develop customer insights, incorporate external data sources such as competitive insights and weather data, analyse shopping histories, interpret and categorise behaviours and create actionable insights and customer specific personalisation.
Or in simple words, ML can help you find hidden knowledge in available consumer data to streamline your digital marketing processes.
Machine learning tips for SEO
In this session by Britney Muller, you’ll understand machine learning basics, what ML can be used for, examples of ML solving SEO tasks and executable programs you can start using immediately.
Who is Britney Muller?
Data is Britney’s yellow brick road. She knows just how to optimise businesses online and offline conversion rates through in-depth geo-local target market and customer acquisition research. Britney Muller stays on top of her game by pivoting strategy month-by-month via google analytic evaluations, taking any new algorithmic changes into effect, dynamic targeting, A/B testing, eye tracking and multi-channel content evaluations.