Beginners guide to SEO in machine learning 

With machine learning and big data, Google has been able to more effectively figure out what a searcher needs and how to deliver it to them.

With machine learning’s power, searches will become concept-driven instead of keyword-driven. Misspellings, misidentifications, and garbled mixtures of words typed by people who still aren’t sure how the internet works will be utilised alchemy-like into search engine gold by Google’s predictive algorithms.

If you make high rankings with high bounce rates by fooling unsuspecting searchers, those rankings will fall off the bottom of people’s computer screens.  

What is Machine Learning?

“Machine Learning” is a process of data analysis that provides a mechanism to not only examine your data but also study from the analysis to enhance future methods and objectives of the analysis. In traditional programming, computer scientists are required to manually enter code and program analytics. 

Machine learning is a kind of AI that practices statistics for programming in a way that enables machines to “learn” without someone manually banging away at a keyboard. It is a more agile, more effective way of programming. 

When Google launched machine learning for Google Translate, the system took about as much in a day as it had improved in the earlier decade.

How Google’s Machine Learning Affects SEO

1. Concept-based HTML Tags

2. Links, Clicks through, and Bounce rates

3. Width of content

How You Can Use Machine Learning to Advance SEO

1. Getting Good Data

2. Analyzing the data 

3. The machine learning feedback loop

4. Improve customer experience

5. Keyword research.

6. Technical audits.

7. Content optimization.

8. Content distribution.

9. Internal linking.