Predictive Modeling and Machine Learning with MATLAB Online Course & Certification- GoLearning powered by e&

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Level Professional
المدة 22 ساعات hours
الطبع بواسطة MathWorks
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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.

الوحدات

Introduction to Supervised Machine Learning

3 Videos

3 Readings

Show info about module content

3 Videos

Practical Data Science with MATLAB
Instructor Introduction
Introduction to Supervised Machine Learning

3 Readings

Access MATLAB
Data and Code Files
Supervised Machine Learning Reference

Data Processing and Feature Engineering

2 Videos

2 Readings

1 Discussion

1 Assignment

Show info about module content

1 Assignment

Feature Engineering Review

1 Discussions

More Features, More Questions

2 Videos

Introduction to the Taxi Data
Creating and Cleaning Features

2 Readings

Introduction to Module 1
Variables in the Taxi Data

Exploring Regression Models

2 Videos

2 Readings

1 Assignment

Show info about module content

1 Assignment

Train a Regression Model

2 Videos

Introduction to Regression
Using the Regression Learner App

2 Readings

Note regarding updates to MATLAB
Summary of Regression Models

Training and Evaluating Regression Models

4 Videos

1 Readings

4 ExternalTool

1 Assignment

Show info about module content

1 Assignment

Apply the Regression Workflow

4 External Tool

Practice with Linear Regression Models
Practice with Regression trees
Practice Calculating R²
Practice Comparing Models

4 Videos

Customizing Model Parameters
Evaluating Regression Models
Evaluate Your Model in MATLAB
Summary of Regression

1 Readings

Regression Metrics

Exploring Classification Models

2 Videos

3 Readings

1 Assignment

Show info about module content

1 Assignment

Train a Classification Model

2 Videos

Introduction to Classification
Using the Classification Learner App

3 Readings

Introduction to Module 2
Note regarding updates to MATLAB
Summary of Classification Models

Evaluating Classification Models

2 Videos

2 Readings

1 Discussion

Show info about module content

1 Discussions

Can you improve the model?

2 Videos

Evaluating Classification Models
Evaluating Classification Models in MATLAB

2 Readings

Binary Classification Metrics Reference
Evaluate and Customize Classification Models

Training and Evaluating Multiclass Models

2 Videos

2 Readings

1 Assignment

Show info about module content

1 Assignment

Apply The Classification Workflow

2 Videos

Training a Multiclass Model
Summary of Classification

2 Readings

Multiclass Classification Metrics Reference
Customizing Multiclass Models

Using Validation Data to Improve Model Generalization

2 Videos

3 Readings

Show info about module content

2 Videos

Addressing Underfitting and Overfitting
Using Validation Data During Training

3 Readings

Introduction to Module 3
Examining Bias Variance Trade-off
Practice Partitioning Data

Reducing Model Complexity

2 Videos

1 Readings

1 Discussion

1 Assignment

Show info about module content

1 Assignment

Practice Reducing Model Complexity

1 Discussions

Share Your Model Results

2 Videos

Embedded Methods for Feature Selection
Using Regularization to Prevent Overfitting

1 Readings

Using Wrapper Methods to Select Features

Creating Ensemble Models

2 Videos

1 Assignment

Show info about module content

1 Assignment

Applying Ensemble Models

2 Videos

Introduction to Ensemble Models
Training Ensemble Models

Tuning Model Parameters

4 Videos

Show info about module content

4 Videos

Introduction to Hyperparameters
Optimizing Hyperparameters
Evaluating and Using Your Model
Summary of Module 3

Project: Apply the Supervised Machine Learning Workflow

1 Readings

2 Assignment

Show info about module content

2 Assignment

The Supervised Machine Learning Workflow
Mini-Project: Predicting Taxi Demand

1 Readings

Setup for Mini-Project: Predicting Taxi Demand

Reducing Prediction Errors

2 Videos

4 Readings

1 Assignment

Show info about module content

1 Assignment

Practice Reducing Prediction Errors

2 Videos

Handling Class Imbalance
Reducing Specific Errors Using Cost Matrices

4 Readings

Introduction to Module 4
Sampling Data
Practice Handling Class Imbalance
Oversampling the Minority Class

Using Your Model and Next Steps

3 Videos

3 Readings

1 Discussion

1 Assignment

Show info about module content

1 Assignment

Quiz: Advanced Topics and Next Steps

1 Discussions

How will you use your models?

3 Videos

Integrating Your Model
A Discussion with Heather
Summary of Predictive Modeling and Machine Learning

3 Readings

Examples of Integrating Machine Learning Models
Automated Machine Learning
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Unlock the power of MATLAB in "Predictive Modeling and Machine Learning with MATLAB," a professional-level course by Coursera. Ideal for data science and AI enthusiasts with some statistical knowledge, this course teaches you to prepare data, train, evaluate, and improve predictive models over 1320 minutes. Subscription options include Starter, Professional, and Paid. Perfect for professionals looking to enhance their machine learning skills.