An Experiment To Try To Predict Google Rankings

Machine learning is quickly becoming an indispensable tool for many large companies. Everyone has for sure heard of google’s ai algorithm beating. The world champion in go, as well as technologies like rankbrain. But machine learning doesn’t have to be a mystical topic relegated to the realm. Mathematics researchers. There are many libraries and technologies available that promise. To be very useful to any industry that has data to play with.Machine learning also has the ability to transform traditional website marketing and SEO.

Late last year my colleagues and I (rather naively)

Late last year, my colleagues and I (rather naively) started an experiment in which we ran several popular machine Peru WhatsApp Number List learning algorithms to predict rankings in Google. We ended up with an assembly that scored 41% true positives and 41% true negatives on our data set. In the following paragraphs, I’ll walk you through our experience, and I’ll also discuss a few important libraries and technologies that are important for SEOs to start understanding. Our experience Towards the end of 2015, we started to hear more and more about machine learning and its promise to use large amounts of data.

The more we dug, the more technical it became

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The more we dug the more technical it became. And it quickly became clear that it would be helpful if someone helped us navigate this world. Around this time. We came across a brilliant data scientist from brazil named alejandro simkievich. The interesting thing for us about simkievich was that he worked in search relevance and conversion. Rate optimization (cro) and ranked highly for major kaggle contests. (for those of you unfamiliar. Kaggle is a website that hosts machine learning competitions for groups of data scientists. And machine learning enthusiasts.)simkievich owns statec. A data science/machine learning consulting firm, with clients in the consumer goods automotive.

 

 

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