Mathematics for Machine Learning: Multivariate Calculus by Imperial College London
This course, one of the top Online Courses to Learn about Math and Logic, provides a basic understanding of multivariate calculus, which is essential to construct several standard machine learning approaches. You will start at the beginning with a review of the "rise over run" formulation of a slope before moving on to the formal definition of a function's gradient. Then you begin to put together a collection of tools that make calculus easier and faster. Then you will learn how to calculate vectors that point uphill on multidimensional surfaces and use an interactive game to demonstrate it.
You look at how calculus may help you to develop approximations to functions and measure how precise those approximations should be. You also spend some time discussing where calculus is used in neural network training before showing you how it is used in linear regression models. This course is designed to provide you a basic grasp of calculus as well as the vocabulary you'll need to look up concepts when you get stuck. Without getting into too much depth, hopefully you'll have enough confidence to take some more specialized machine learning classes in the future.
This course offers:
- Flexible deadlines: Reset deadlines in accordance to your schedule.
- Certificate : Earn a Certificate upon completion
- 100% online
- Beginner Level
- Approx. 18 hours to complete
- Subtitles:Arabic, French, Portuguese (European), Greek, Italian, Vietnamese, German, Russian, English, Spanish
- Course 2 of 3 in the Mathematics for Machine Learning Specialization
Coursera Rating: 4.7/5
Enroll here:https://www.coursera.org/learn/multivariate-calculus-machine-learning
