In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB and Data Processing and Feature Engineering with MATLAB to increase your ability to harness the power of MATLAB to analyze data relevant to the work you do.
Predictive Modeling and Machine Learning with MATLAB
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Predictive Modeling and Machine Learning with MATLAB
This course is part of Practical Data Science with MATLAB Specialization
Instructors: Michael Reardon
15,762 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.8
(116 reviews)
Beginner level
No prior experience required
18 hours to complete
3 weeks at 6 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Apply a full machine learning workflow, from cleaning data to training & evaluating models using a real-world dataset
Use apps to quickly train many machine learning models to find the best approach for your application
Customize training using cost matrices to emphasize important classes
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
11 assignments
Taught in English
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This course is part of the Practical Data Science with MATLAB Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
In this module you'll apply the skills gained from the first two courses in the specialization on a new dataset. You'll be introduced to the Supervised Machine Learning Workflow and learn key terms. You'll end the module by creating and evaluating regression machine learning models.
What's included
11 videos8 readings3 assignments4 app items1 discussion prompt
In this module you'll learn the basics of classification models. You'll train several types of classification models and evaluation the results.
What's included
6 videos7 readings2 assignments1 discussion prompt
In this module you'll apply the complete supervised machine learning workflow. You'll use validation data inform model creation. You'll apply different feature selection techniques to reduce model complexity. You'll create ensemble models and optimize hyperparameters. At the end of the module, you'll apply these concepts to a final project.
What's included
10 videos5 readings4 assignments1 discussion prompt
What's included
5 videos7 readings2 assignments1 discussion prompt
Offered by
Recommended if you're interested in Machine Learning
Duke University
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University of Illinois Urbana-Champaign
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Frequently asked questions
Yes. A free license to MATLAB Online is available to learners enrolled in the course. You can view the supported browsers here.
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.