Predictive Modeling and Machine Learning with MATLAB

 

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

Build your subject-matter expertise

• 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.

• Learn new concepts from industry experts

• Gain a foundational understanding of a subject or tool

• Develop job-relevant skills with hands-on projects

• Earn a shareable career certificate

There are 4 modules in this course

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.
These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background. To be successful in this course, you should have some background in basic statistics (histograms, averages, standard deviation, curve fitting, interpolation) and have completed courses 1 through 2 of this specialization. By the end of this course, you will use MATLAB to identify the best machine learning model for obtaining answers from your data. You will prepare your data, train a predictive model, evaluate and improve your model, and understand how to get the most out of your models.

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