How many times have you heard a company tell you they're using 'Machine Learning.' But, then you're not quite sure how they're using it.
There is a lot of talk about Machine Learning today, but it's hard to grasp how it will impact both our jobs and lives.
In this episode of the GrowthTLDR, we talk to Brittney Muller, SEO Scientist at the wonderful Moz all about Machine Learning.
We talk
- How Britney became fascinated by Machine Learning, and we give you a bunch of resources to get started with and improve your knowledge.
- What are some practical use cases for Machine Learning in the world of search and marketing?
- Why learning about Machine Learning can help you reframe the way you look at problems and opportunities, plus some examples of how machine learning is making the world a better place.
Happy Growing!
Time Stamped Notes
[2:15] - We talk about chess and why it's a great thing to learn
[4:10] - We talk about the evolution of machine learning and when/if it's going to terminate us :)
[5:45] - Britney tells us about some of the first use cases that got her into machine learning. She discovered Harvard's CS109 Data Science course online. She went through the homework tasks and would email back and forth with the people responsible for the course about the homework questions.
[8:20] - The most common resource Britney sends people to is Codelabs by Google. It walks you through the step-by-step of machine learning. One of the best places to start is learning about 'Tensorflow' on Codelabs.
[10:07] - TensorFlow is Google's framework for machine learning. It's the foundation on which you can build machine learning models.
[10:55] - You don't necessarily need a background in coding to learn how to build machine learning models. There are now incredible tools to help you get started. Britney gives us some examples.
[12:25] - We talk about great uses of machine learning to freak your friends out via their phones :)
[14:25] - Britney gives us some of the best online sources to learn more about machine learning, including - Instructables, KDnuggets , Kaggle.
[16:25] - Moz is looking at machine learning to establish the intent of a keyword by looking at Google's search result pages. For example, ads could help determine a keyword is transactional, whereas review sites could determine the intent of the keyword is comparative.
[19:45] - Britney gives us some great examples of how people are using automation in SEO. For example, someone built a script that pulls data from Google Search Console, looks for low performing pages, identifies that pages best performing keyword, checks if the keyword is in the page title, and if it isn't it adds it.
[22:35] - Instead of learning to code, Britney recommends finding models and scripts that already exist for the problem you want to solve with machine learning. The best way to learn is to get started and play around with real applications of machine learning.
[25:10] - Learning about the basics of machine learning helps you to start seeing problems and opportunities through a new lens. It can benefit you in many ways.
[28:00] - Britney talks about some of the applications of machine learning that will make the world a better place, from detecting illegal deforestation, stopping elephant poaching, to helping wipe out malaria. Britney gets excellent ideas from Intellectual Ventures, a company founded by Bill Gates that hires hackers to solve real-world problems.
[34:10] - We end by talking about how machine learning will affect the role of marketers over the next ten years.
– Britney on LinkedIn / Twitter
– Kieran on Twitter / LinkedIn / Medium
– Scott on Twitter / Linked / Medium
