Introduction to Machine Learning
Machine learning models learn, identify patterns, and make decisions with minimal intervention from humans. Ideally, machines increase accuracy and efficiency and remove (or greatly reduce) the possibility of human error.
In this course, students will learning about unsupervised and supervised learning methods and associated use cases. The three algorithms covered include: classification, regression, and clustering and hands-on projects will be used to demonstrate concepts.
Who Is This Course For?
data scientists, data analysts, programmers, problem solvers, coders
What Will You Learn?
How to use regression to make predictions based on existing data.
How to use clustering to find hidden groups or segments that exist in a data set.
How to use classification to predict which data fits into a specific class.
How to distinguish between unsupervised and supervised learning.
Prerequisite
Python for Data Analytics
Duration
15 hours
Cost
$499.00
Course Schedule:
This course is not currently scheduled. Please sign up if you want to get this course soon.