Mathematics for Machine Learning by Imperial College London
Mathematics for Machine Learning: Multivariate Calculus
Imperial College of London
Overview
Imperial College of London is organizing an online course on Mathematics for Machine Learning: Multivariate Calculus, This course is going to be very useful for the Students/Faculty who are interested in Machine learning, Deep Learning, and data science. Well, this is the main problem with the students of CSE they always learn the ML but mathematics behind it very few of them knows, so If you want to become a machine learning engineer and wanna pursue research in this field, Join this course, Enroll now for free of cost, You will get the 7 days free access. This course will be on the Coursera platform. This is a beginner trach course so anyone can join this course.
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.
Skills
You will learn the following skills in this online course on Mathematics for Machine Learning: Multivariate Calculus by Imperial College of London:
- Linear Regression
- Vector Calculus
- Multivariable Calculus
- Gradient Descent
Features
There are the following features in this online course:
- Shareable Certificate
- Earn a Certificate upon completion
- 100% online
- Start instantly and learn at your own schedule
- Flexible deadlines
- Reset deadlines in accordance with your schedule.
- Beginner Level
- Approx. 18 hours to complete
- English
- Subtitles: English, Greek, Spanish
Speaker
- A. Freddie Page, Strategic Teaching Fellow, Imperial College London
- Samuel J. Cooper, Lecturer, Imperial College London
- David Dye, Professor of Metallurgy, Imperial College London
Topics
The topics of this course are not limited to
- What is calculus? 4 hours
- Multivariate calculus 3 hours
- Multivariate chain rule and its applications 3 hours
- Taylor series and linearisation 3 hours
- Intro to optimization 2 hours
- Regression 2 hours
How to apply
Interested candidate who wants to join this course can join by the following link;