Description
Course info
Rating
(213)
Level
Beginner
Updated
February 17, 2016
Duration
1h 25m
Description

In this course, you will learn how developers and Data Scientists use Machine Learning to predict events based on data. Specifically, how to format your problem to be solvable, where to get data, and how to combine that data with algorithms to create models that can predict the future. Throughout this course we will use R, one of the best known Machine Learning languages. No previous R experience is required.

About the author
About the author

Jerry Kurata is a Solutions Architect at InStep Technologies.

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Transcript
Transcript

Hi, my name is Jerry Kurata and welcome to my course Understanding Machine Learning with R͟.

These days, Machine Learning is all around us. From helping doctors diagnose patients to detecting fraudulent credit card transactions. We likely encounter machine learning applications a dozen times a day and may not realize it. It silently scans our inboxes for spam emails, and makes sure we see an ad on every web page for the shoes we looked at last week.

[Note: the slides should contain the bullet points in orange only. The black is the voice over narration.]

This course will:

  • Introduce you to Machine

    Learning Introduces you to Machine Learning and the technology behind it. You will see why companies are in such a rush to use Machine Learning to grow their business and increase profits.
  • Teach you to build predictive models

    You will learn how developers and Data Scientists use Machine Learning to predict events based on data. Specifically, how to format your problem to be solvable, where to get data, and how to combine that data with algorithms to create models that can predict the future.
  • Utilize the R language

    Throughout this course we use the R language. R is the best known Machine Learning language. We utilize R and its libraries to make it easy to build and test Machine Learning solutions. However, you do not need prior R experience.
In this course we learn by doing, and the R code we use will be explained in the examples. By the end of this course you will know the how, when, and why of building a machine learning solution. And have the skills you need to transform a one line problem statement into a tested prediction model that solves the problem.