Mathematics for Machine Learning: Multivariate Calculus
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Mathematics for Machine Learning: Multivariate Calculus at Coursera Overview
Duration | 18 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Mathematics for Machine Learning: Multivariate Calculus at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 2 of 3 in the Mathematics for Machine Learning Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Beginner Level
- Approx. 18 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Greek, Italian, Vietnamese, German, Russian, English, Spanish
Mathematics for Machine Learning: Multivariate Calculus at Coursera Course details
- This course offers a brief introduction to the multivariate calculus required to build many common machine learning techniques. We start at the very beginning with a refresher on the ?rise over run? formulation of a slope, before converting this to the formal definition of the gradient of a function. We then start to build up a set of tools for making calculus easier and faster. Next, we learn how to calculate vectors that point up hill on multidimensional surfaces and even put this into action using an interactive game. We take a look at how we can use calculus to build approximations to functions, as well as helping us to quantify how accurate we should expect those approximations to be. We also spend some time talking about where calculus comes up in the training of neural networks, before finally showing you how it is applied in linear regression models. This course is intended to offer an intuitive understanding of calculus, as well as the language necessary to look concepts up yourselves when you get stuck. Hopefully, without going into too much detail, you?ll still come away with the confidence to dive into some more focused machine learning courses in future.
Mathematics for Machine Learning: Multivariate Calculus at Coursera Curriculum
What is calculus?
Welcome to Multivariate Calculus
Welcome to Module 1!
Functions
Rise Over Run
Definition of a derivative
Differentiation examples & special cases
Product rule
Chain rule
Taming a beast
See you next module!
About Imperial College & the team
How to be successful in this course
Grading Policy
Additional Readings & Helpful References
Matching functions visually
Matching the graph of a function to the graph of its derivative
Let's differentiate some functions
Practicing the product rule
Practicing the chain rule
Unleashing the toolbox
Multivariate calculus
Welcome to Module 2!
Variables, constants & context
Differentiate with respect to anything
The Jacobian
Jacobian applied
The Sandpit
The Hessian
Reality is hard
See you next module!
Practicing partial differentiation
Calculating the Jacobian
Bigger Jacobians!
Calculating Hessians
Assessment: Jacobians and Hessians
Multivariate chain rule and its applications
Welcome to Module 3!
Multivariate chain rule
More multivariate chain rule
Simple neural networks
More simple neural networks
See you next module!
Multivariate chain rule exercise
Simple Artificial Neural Networks
Training Neural Networks
Taylor series and linearisation
Welcome to Module 4!
Building approximate functions
Power series
Power series derivation
Power series details
Examples
Linearisation
Multivariate Taylor
See you next module!
Matching functions and approximations
Applying the Taylor series
Taylor series - Special cases
2D Taylor series
Taylor Series Assessment
Intro to optimisation
Welcome to Module 5!
Gradient Descent
Constrained optimisation
See you next module!
Newton-Raphson in one dimension
Checking Newton-Raphson
Lagrange multipliers
Optimisation scenarios
Regression
Simple linear regression
General non linear least squares
Doing least squares regression analysis in practice
Wrap up of this course
Did you like the course? Let us know!
Linear regression
Fitting a non-linear function
Mathematics for Machine Learning: Multivariate Calculus at Coursera Admission Process
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