Learn how to create and release your own library and take your first steps with machine learning
This course aimed at students with beginner to intermediate skill in F#, basic understanding of the F# syntax and a light functional understanding would be beneficial. You'll also need a computer with Linux, OSX or Windows with F# installed and an internet connection.
Have you wanted to understand how to 'do' machine learning or implement algorithms from a textbook in a programming language, or deploy a library to Nuget? Well, this course includes sections on machine learning using a mathematical theorem known as Bayes' Theorem.
What will we do?
We will complete two F# project together,
We will start by creating a predictive text engine and deploy it to Nuget, while learning how to write some basic unit tests in FsUnit. We will explore every line of code together and point out all the important programming concept as we progress.
Then we will use Bayes' Theorem to classify spam messages using real world data. We'll build a command line application and parse command line arguments so that we can use our program on the command line.
What is f#?
F# is a mature, functional-first language especially well suited to computer science, machine learning, distributed computing and web applications too. There really is no limit to what F# can do for you!
We’ve structured the course to make learning all the material as easy and accessible as possible. We’ll challenge you to complete an F# programming task in every video to make sure you’ve got a great grip on all the concepts. But don’t worry, because after every challenge, we’ll also walk you through a solution line by line.
We have structured the course to introduce you to some computer science concepts, but to also encourage you to spend your own time to gain further insights into the concepts we introduce you to.
- 847.5 MB
- Update Date:
- Jason Stafford
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