We've walked through a number of different examples of artificial intelligence and machine learning in the real world and we did take one in-depth look at how I built out the recommendation engine for dev camp along with even seeing some of the logic behind counting the words in the content and then building weights off of those.

Now what you're going to build out or what you are going to write about is nothing highly technical. We haven't gone through the algorithms yet so you wouldn't even be able to know exactly how that works but instead what I want you to do because the entire goal of this section and of the entire course is for you to build a mental framework so that you start thinking like a machine learning and a data scientist type of developer.

And this is one of the first stages so you are going to pick out something in the real world. It could be if you are working full time right now and you're working in an industry pick out that industry or if there is some other industry or product that you think could use some type of machine learning then pick that out and then I want you to describe how you would learn so how you would build a system that would learn. And one of the easiest ways of doing that is think about if your brain was limitless kind of close to a computer.

There are still limits but think if you have the ability to process millions of pieces of data in a second just like a computer is able to do how you would build out that machine learning type of system. You don't have to get into algorithms you don't have to get into a statistics or anything like that. I simply want you to have and develop a high-level understanding of the process.

Remember when I talked about how the most critical things that you can think about whenever you're building out a machine learning system is knowing the inputs and outputs and so that would be my recommendation is to start there. Think about that product or that industry. Think about all of the various inputs and then what the desired output would be.

If you're working for a company and you want to predict which leads are most likely to turn into customers talk about the different data types that are inside of your lead data whether it's how much money they make their education any kind of data that you have on those leads and then try to predict exactly who the ideal lead is that could translate into being a customer.

That's just one example. Please don't take that identical example because I want you to go into detail the entire purpose of this is so that you can start thinking in a very input and output oriented mindset and before you get upset about having to write a paper in the course like this.

I am very intentional when I'm picking this out as a homework assignment. I have spoken with a large number of hiring partners I'm on the board of a tech panel up in Utah and one of the most common complaints I get from hiring partners is that the developers that they're hiring the machine learning developers the data scientists the web developers. One of their biggest weaknesses is they don't have the right communication skills.

They're not simply talking about just being nice or polite or anything like that they're talking about if they are given a project they are able to communicate what they're wanting to do properly. So they have a hard time summarizing the issue summarizing their solution in a way that all of the stakeholders can understand. And so we're going to do a large number of projects like this because it's going to help you improve not only as a developer and in how you understand this overall machine learning ecosystem but it's also going to help you to learn how to communicate those ideas to other people so that they can understand.