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Complete MATLAB Course: Beginner to Advanced!

If you would like to get started using MATLAB, you are going to LOVE this 4+ hour video course! Go from beginner to advanced with tutorials covering basic MATLAB programming, loading and saving data, data visualization, signal & image processing and data science applications.

If you enjoy this tutorial series, feel free to check out The Complete MATLAB Course Bundle! Get access to 5 courses covering MATLAB for absolute beginners, machine learning for data science, data pre-processing, app designing using the GUIDE and designer utilities and more!

For a limited time, you can get FREE access to our most popular MATLAB course on Teachable! Enroll now using the link below:

Below is a list of topics covered in this MATLAB course:

  • What is Matlab, how to download Matlab, and where to find help
  • Introduction to the Matlab basic syntax, command window, and working directory
  • Basic matrix arithmetic in Matlab including an overview of different operators
  • Learn the built in functions and constants and how to write your own functions
  • Solving linear equations using Matlab
  • For loops, while loops, and if statements
  • Exploring different types of data
  • Plotting data using the Fibonacci Sequence
  • Plots useful for data analysis
  • How to load and save data
  • Subplots, 3D plots, and labeling plots
  • Sound is a wave of air particles
  • Reversing a signal
  • The Fourier transform lets you view the frequency components of a signal
  • Fourier transform of a sine wave
  • Applying a low-pass filter to an audio stream
  • To store images in a computer you must sample the resolution
  • Basic image manipulation including how to flip images
  • Convolution allows you to blur an image
  • A Gaussian filter allows you reduce image noise and detail
  • Blur and edge detection using the Gaussian filter
  • Introduction to Matlab & probability
  • Measuring probability
  • Generating random values
  • Birthday paradox
  • Continuous variables
  • Mean and variance
  • Gaussian (normal) distribution
  • Test for normality
  • 2 sample tests
  • Multivariate Gaussian

Happy learning!

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Data Preprocessing for Machine Learning Using MATLAB + FREE Udemy Coupon!

Enroll for FREE on Udemy using the coupon below!

This course is for you if you want to fully equip yourself with the art of applied machine learning using MATLAB. We will apply the most commonly used data preprocessing techniques without having to learn all the complicated maths. Additionally, if you have had previous hours and hours of machine learning implementation but could never figure out how to further improve the peformance of the machine learning algorithmsBy the end of this course, you will have at your fingertips a vast variety of the most commonly used data preprocessing techniques that you can use instantly to maximize your insight into your data set.

Get The Complete MATLAB Course Bundle for 1 on 1 assistance!

The Complete MATLAB Course Bundle!

In this particular tutorial we will cover the following topics:

  • Introduction to the course
  • Introduction to MATLAB
  • Importing a data-set into MATLAB
  • Deletion strategies
  • Using mean and mode
  • Considering as a special value
  • Class specific mean and mode
  • Random value imputation


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Machine Learning for Data Science Using MATLAB

Get The Complete MATLAB Course Bundle for 1 on 1 help!

The Complete MATLAB Course Bundle!

Enroll in the 5 courses directly on Udemy!

Create Apps in MATLAB with App Designer
MATLAB App Designing: The Ultimate Guide for MATLAB Apps
Data Analysis with MATLAB for Excel Users
Complete MATLAB Tutorial: Go from Beginner to Pro
Advanced MATLAB Data Types and Data Structures
Machine Learning for Data Science Using MATLAB

This course is for you if you want to have a real feel of the Machine Learning techniques without having to learn all of the complicated math. Additionally, this course is also for you if you have had previous hours of machine learning theory but could never figure out how to implement and solve data science problems with it.

The approach in this course is very practical and we will begin with the basics. We will immediately start coding after a couple of introductory tutorials and we try to keep the theory to bare minimal. All of the coding will be done in MATLAB which is one of the fundamental programming languages for engineer and science students, and is frequently used by top data science research groups world wide.

Below is a complete list of topics covered in the video. You will find the timestamps on YouTube.

    • Introduction
    • Intro to MATLAB
    • Intro to Data Preprocessing
    • Importing Data into MATLAB
    • Handling Missing Data Part 1
    • Handling Missing Data Part 2
    • Feature Scaling
    • Outliers Part 1
    • Outliers Part 2
    • Dealing with Categorical Data Part 1
    • Dealing with Categorical Data Part 2
    • Data Preprocessing Template