Ementorhub

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

Statistical Modeling

Machine Learning

Predictive Analytics

Predictive Modeling

Regression Analysis

Matlab

Data Processing

Classification And Regression Tree (CART)

Supervised Learning

Applied Machine Learning

Sampling (Statistics)

Feature Engineering

There are 4 modules in this course

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.

Creating Classification Models

Applying the Supervised Machine Learning Workflow

Advanced Topics and Next Steps