Many marketers and computer scientists are converging on the importance of machine learning. While most courses will teach you the statistics behind machine learning models, very few show you a hands on demonstration to building your own machine learning application. In this courses, we’ll take you through the necessary steps to building your very own machine learning application.
You should take this course if:
You are a data scientist or data insight professional who has never build a machine learning application before.
You are a data scientist or data insight professional who understands the math behind machine learning, but doesn’t understand the programming elements.
You are interested in a courses with hands on directions to building your very first application.
Follow a Structured Curriculum
Introduction to python and R
In this section, you’ll learn about the two programming language most data scientists and data insight professional use.
In this section, you’ll pick your statistical model. Each model is related to specification end goals you may have, such as classification or clustering.
Picking your statistical model
Training and test sets
In this section, you’ll learn how to take your data and break it up into training and test sets. You will also learn about other methods such as resampling and cross validation.
In this section, you’ll learn about the types of statistics run on your models to see which model performed the best. A number of comparison statistics will be reviewed.
Model comparison
Ready to Continue your Education?
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