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$1,456 pledged of $2,500 goal
By Richard Han
$1,456 pledged of $2,500 goal


Would you like to learn the mathematics behind machine learning? There aren't many resources out there that give simple detailed examples and that walk you through the topics step by step.  If you're looking to gain a solid foundation in machine learning, allowing you to study on your own schedule at a fraction of the cost it would take at a traditional university, to further your career goals, this online course is for you. If you're a working professional needing a refresher on machine learning or a complete beginner who needs to learn machine learning for the first time, this online course is for you.  

Why you should take this online course: You need to refresh your knowledge of machine learning for your career to earn a higher salary. You need to learn machine learning because it is a required mathematical subject for your chosen career field such as data science. You intend to pursue a masters degree or PhD, and machine learning is a required or recommended subject.  

In this course, I cover core topics such as:  

  • Linear Regression
  • Logistic Regression
  • Linear Discriminant Analysis
  • Artificial Neural Networks
  • Support Vector Machines

After taking this course, you will feel CARE-FREE AND CONFIDENT. I will break it all down into bite-sized no-brainer chunks. I explain each definition and go through each example STEP BY STEP so that you understand each topic clearly. I will also be AVAILABLE TO ANSWER ANY QUESTIONS you might have on the lecture material or any other questions you are struggling with. 

Practice problems are provided for you, and detailed solutions are also provided to check your understanding. 30 day full refund if not satisfied. 

Pledge now!

Risks and challenges

I have created most of the lecture material. I am still adding example problems and creating practice problems. I hope to make the course so much better by giving simple examples.

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    Pledge $50 or more About $50

    Kickstarter Special

    Get the full course, including video lectures, practice problems and solutions.
    Topics covered:
    Linear regression
    Logistic regression
    Linear discriminant analysis
    Artificial neural networks
    Support vector machines

    Estimated delivery
    27 backers
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Funding period

- (60 days)