Hey it's Bruno here.
Thanks a lot for taking care of little Timmy.
He said he had a lot of fun with you and he said that you're pretty cool.
Anyway let's get back to work.
We have a big client here big hospital client and they've heard about machine learning and they're willing
to invest some money in experimenting with machine learning and seeing if we can build a model for them
that might help their doctors.
They have some data on heart disease and they want to see if we can build a model that will be worthwhile
to them.
So can you create a report for them.
They're not very good with machine learning so obviously the more information we can provide them and
not make it too technical the better it is you can do that.
You're the best.
All right everybody.
We just came off from a really tough section which was psychic learn it was a lot to learn.
We know that.
I remember when I first learned so I could learn.
It was extremely overwhelming.
I felt like I will never ever understand the entire library.
But as you saw what Daniel does is he goes to the documentation.
He searches Google anytime he has questions.
He looks for the answer.
That's part of our skill as programmers are as data scientists.
We're able to solve problems that other people might have difficulties with.
We're problem solvers.
So over this project we're going to repeat what we did with so I could learn but actually formalize
it inside of a project so that now we have the skills and the tools necessary for us to build models
around real world problems.
And we're going to build it in a way that actually mimics real life work.
So some of these reports are actual reports that Daniel and I have worked with before and you can use
these reports and this methodology to demonstrate to your future employers why they should hire you
or use it in your current role as a template for any future problems.
But we've got a lot to cover so let's get started.