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Basic Course Description

This courseis for youif you want tofully equip yourself with the art of applied machine learning using MATLAB. This course is also for you if you want to apply the most commonly used data preprocessing techniques without having tolearnall the complicatedmaths. Additionally, thiscourse is also for youif you have had previous hours and hours ofmachine learning implementationbut could never figure out how to further improve the peformance of the machine learning algorithms.By the end of this course, you will have at your fingertips, a vast variety of most commonly used data preprocessing techniques that you can use instantly to maximize your insight into your data set.

The approach in this course is very practicalandwe will start everything from veryscratch. We will immediately start coding after a couple of introductory tutorialsand we try to keep the theory to bare minimal. All the coding will be done in MATLAB which is one of the fundamental programming languages forengineer and science studentsand is frequently used by top data science research groups world wide.

Below is the briefoutline of this course.

Segment 1: Introduction to course and MATLAB

Segment 2: Handling Missing Values

Segment 3: Dealing with Categorical Variables

Segment 4: Outlier Detection

Segment 5: Feature Scalling and Data Discretization

Segment 6: Project: Selecting Techniques for your Dataset


Your Benefits and Advantages:

  • If you do not find the course useful, you are covered with30 day money back guarantee, full refund, no questions asked!

  • You will be sure of receiving quality contents since the instructorshas already manycoursesin the MATLAB on udemy.

  • You havelifetime access to the course.

  • You haveinstant and free access to any updatesi add to the course.

  • You have access to allQuestions anddiscussionsinitiated by other students.

  • You will receivemy supportregarding any issues related to the course.

  • Check out the curriculum andFreely available lecturesfor a quick insight.

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It's time to takeAction!

Click the "Take This Course" button at the top right now!

...Time is limited andEvery second of every day is valuable...

We are excited to see youin the course!

Best Regrads,

Dr. Nouman Azam

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More Benefits and Advantages:

You receiveknowledge from an experiencedinstructor(Dr. Nouman Azam) who is thecreatorofmanycourses on Udemy in the MATLAB niche.

The titles of these courses are

  • Machine Learning for Data Science using MATLAB

  • Machine Learning Classification Algorithms using MATLAB

  • Complete MATLAB Tutorial: Go from Beginner to Pro

  • MATLAB App Desigining: The Ultimate Guide for MATLAB Apps

  • Create Apps in MATLAB with App Designer (Codes Included)

  • Advance MATLAB Data Types and Data Structures

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Student Testimonials for Dr. Nouman Azam!

This is the second Udemy class on Matlab I've taken. Already, a couple important concepts have been discussed that weren't discussed in the previous course. I'm glad the instructor is comparing Matlab to Excel, which is the tool I've been using and have been frustrated with. This course is a little more advanced than the previous course I took. As an engineer, I'm delighted it covers complex numbers, derivatives, and integrals. I'm also glad it covers the GUI creation. None of those topics were covered in the more basic introduction I first took.

Jeff Philips

Great information and not talking too much, basically he is very concise and so you cover a good amount of content quickly and without getting fed up!

Oamar Kanji

The course is amazing and covers so much. I love the updates. Course delivers more then advertised. Thank you!

Josh Nicassio

Student Testimonials! who are also instructors in the MATLAB category

"Concepts are explained very well, Keep it up Sir...!!!"

Engr Muhammad Absar Ul Haq instructor of course "Matlab keystone skills for Mathematics (Matrices & Arrays)"

تحديث بتاريخ 14 November, 2018
دورات يمكنك الالتحاق بها على الفور... خذ دورة عبر الإنترنت على Machine Learning ابتداءً من الآن. See all courses

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