Machine Learning

Part 1 Machine learning can seem like an intimidating subject to understand. Typically this would require being proficient at advanced math such as linear algebra, calculus, and statistics. However, even without knowing what goes on under the hood, it’s possible to make use of it to solve business problems. You don’t fully understand every aspect of your car, yet you drive it. The same goes for machine learning. AutoML is a product made by Google, which allows pretty much anyone to use machine learning because it looks at your data and builds a model automatically. The techniques it uses are quite sophisticated, and I won’t be discussing that here. Instead, I’ll focus on being pragmatic and show you how to use it without the math background. We’ll go over an example AI project that reads product reviews and classifies them as either negative or positive. We can then use this to predict whether what someone is saying about our products in other places such as twitter, forum posts, etc are negative or positive. New reviews may then be processed and automatically categorized. ...

Machine learning allows you to take expert judgment, bake it into a mathematical model which can be used to solve similar, but new and different problems. In this short video clip, I highlighted the fact that with little AI development experience, it’s entirely possible to use this technology to build a useful application that solves a real problem. This is a growing field because the potential for return on investment is essentially uncapped at this point. I spent approximately 20 hours self-teaching myself high-level concepts, terminology, understanding how various hyperparameters can influence results, and reviewing the various high-level libraries and components you can utilize that abstract away all the mathematics behind machine learning. I then gave an example of a business problem-solving application that assigns a quantified priority to incoming work, replacing a manual process that typically requires a human. ...