Machine Learning For Dummies

Machine learning is a type of artificial intelligence that has gained a lot of attention in the business world due to its ability to make better predictions over time. Google searches, Netflix recommendations, and even fraudulent transaction alerts are powered by this type of programming.

It is also one of the hardest types of programming to understand, even for programmers. Deepthi Dastari, Sr. Data Scientist at Gogo, gave a talk with Promotable on the basics of machine learning, the basic algorithmic techniques used, when you should consider hiring a data scientist for machine learning skills, and how it can add value to your company.

The Big Takeaways

Most programming runs on rules, but those rules are built on assumptions about data. If a program receives data it cannot understand or understands incorrectly, the program will return incorrect answers. Machine learning is a way to train programs to learn how to handle different kinds of input and adjust its own rules to meet different needs.

Thus, to get the most out of machine learning [22:12], businesses must start with good data, at least tens of thousands of quality data points. That data must then be put into a form that a machine learning platform can use.

Businesses also need to understand that building a model that can deliver new insights takes time to train. Thus, buy-in from senior leadership is crucial. Netflix and Amazon didn’t learn how to make good recommendations overnight. It took quite a long time to train their systems to be as good as they are. Additionally, your models must be measured against business-driven KPIs to evaluate how good they are over time.

This talk will get your feet wet on machine learning, and there are other conversations in the Promotable library about these topics. Explore previous talks on artificial intelligence and data-driven decision making in our archive.