Machine Learning

Free Mini-Course:

Math for Machine Learning Mini-Course

Would you like to learn a mathematics subject that is crucial for many high-demand lucrative career fields such as:

  • Computer Science
  • Data Science
  • Artificial Intelligence

If you’re looking to gain a solid foundation in Machine Learning to further your career goals, in a way that allows you to study on your own schedule at a fraction of the cost it would take at a traditional university, 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 or artificial intelligence. You intend to pursue a masters degree or PhD, and machine learning is a required or recommended subject.

Why you should choose this instructor: I earned my PhD in Mathematics from the University of California, Riverside. I have created many successful online math courses that students around the world have found invaluable—courses in linear algebra, discrete math, and calculus.

In this course, I cover the core concepts such as:

  • Linear Regression
  • Linear Discriminant Analysis
  • Logistic Regression
  • 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 chunksI 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.

Grab a cup of coffee and start listening to the first lecture. I, and your peers, are here to help. We’re waiting for your insights and questions! Enroll now!

Math for Machine Learning Course

Coupon Code: OMTMACHINE

 

Want to try the first module?

Free Mini-Course:

Math for Machine Learning Mini-Course

USE THE COUPON CODE: halfoff

A question many people ask is how they can begin to learn machine learning. First, it would be good to have some background in linear algebra, multivariable calculus, and probability.

Second, there is a good book that is probably easiest to start with: An introduction to statistical learning, by hastie and tibshirani.

There are also some online resources that are helpful: Andrew Ng’s lectures on youtube and the Stanford course by Hastie and Tibshirani.

In the meantime, I wanted to share an interesting TED talk by Jeremy Howard on the wonderful and terrifying implications of computers that can learn. Check it out here: Ted Talk