Four Machine Learning Techniques in Simple Terms

May 28 16:05 2020 Print This Article

Often when you hear experts talk about machine learning and artificial intelligence, it’s easy to feel alienated. A common sentiment we hear from entrepreneurs is that it can be hard to get beyond the buzzwords and grasp the specifics of what ML and AI can actually accomplish.

At Georgian, we’re fortunate to work closely with our portfolio companies to implement many different flavors of ML and AI. We also talk to hundreds of companies every year that are just getting started making their first data science hires. From all of these conversations, we benefit from pattern recognition that helps us recommend techniques to explore.

In this post, our aim is to go a few layers deeper than the overarching terms of ML and AI. We will examine four core business problems that we see many B2B SaaS companies face as they adopt these technologies, share some relatable examples and provide an overview of some impactful techniques that you can consider applying to your business.

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Georgian Partners Blog

Georgian Partners is a thesis-driven growth equity firm investing in business software, Internet and information companies. Founded by successful entrepreneurs and technology executives, Georgian Partners leverages our global software expertise to be able to directly impact the success of companies. Georgian Partners invests in growth-stage enterprise software companies earning $500,000 or more in monthly recurring revenues, or $6 million or more on an annualized basis.

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