# Mathematics for Machine Learning

## Linear Algebra

**Mathematics for Machine Learning,**

## Get a Reminder

Rating | 4.5★ based on 466 ratings |
---|---|

Length | 6 weeks |

Effort | 5 weeks of study, 2-5 hours/week |

Starts | Oct 12 (last week) |

Cost | $49 |

From | Imperial College London via Coursera |

Instructors | David Dye, Samuel J. Cooper, A. Freddie Page |

Download Videos | On all desktop and mobile devices |

Language | English |

Subjects | Data Science Programming Mathematics |

Tags | Data Science Machine Learning Math And Logic |

## Get a Reminder

## Similar Courses

## What people are saying

**
programming assignment
**

Overall good, but some nasty difficulty with the programming assignments... especially the last one.

Programming assignments failed to save and submit sometimes.

Other than the first 2-3 intuition videos and the programming assignment nothing was good in the 5th module/week.

Maybe the programming assignments are far too easy, while some of the quizzes definitely are hard.

The programming assignment do require previous Python/other programming experience.

This course is phenomenal, It helped me to refresh a lot of skills that I learned at my college and at the same time I learned a bit on how to introduce all this matrixes into a programming assignment which are by the way extremely hard because I am a novice at programming.

Although I would have preferred more challenging quizzes and programming assignments the material taught was still world class.

Read more

**
data science
**

I audited the course to gain practical experience and notation reading skills for my data science studies.

Overall, loved this course and highly recommend it to data science enthusiasts taking baby steps towards deep learning.

I would give this course 5 stars for the fact that in five weeks, the course is able to go through perhaps a semester or two or three of Linear Algebra (LA), and how LA fits into data science.

Because I had done a couple other courses on LA relatively recently, some these arcane LA concepts were grasped with some, but not too much, effort.If you are even just a little familiar with LA, this course will give you a good foundation for the LA relative to data science.

(I'm an old-timer, reviewing this material to get up to speed on Machine Learning and Data Science.)

This course can help anyone build a good foundation in Linear Algebra very nice It's a great foundation course for anyone who wants start their journey in Data Science.The content is relevant to ML applications.

The course for every engineer who want to refresh math skills before trying data science.

Read more

**
for machine learning
**

This course is very good to build your fundamental knowledge for machine learning.

Provides a good understanding of Linear Algebra for Machine Learning.

Good material if you want to refresh your knowledge, poor programming assignment support/feedback This is an excellent course for Machine learning foundation.

Mathematics for Machine Learning: Linear Algebra ... REVISED I really liked the pace of this course.

A great course to learn mathematics for machine learning .

If you're looking at refreshing your knowledge of linear algebra for machine learning, this is good course to take.

A good course for gaining knowledge for Linear Algebra for machine learning.

Read more

**
easy to understand
**

Easy to understand material and instructor is great.

I took a great pleasure to study this linear algebra course, teachers are very talented since their way to explain mathematical concepts make it very easy to understand , in fact with this particular amazing approach I changed my perception about learning math and sciences in general.

The best linear algebra courses I ever learnt！ easy to understand A great introduction to linear algebra!

This course makes the Linear Algebra very easy to understand.

Great course Great teacher, great course, easy to understand but still challenging.

The interpretations given for matrix multiplication and change of basis are presented in simple terms which are easy to understand.

The linear algebra was taught in an easy to understand manor but the applications in machine learning were quite sparse This course is a must for all the people who wants to go deep into machine learning and data science as this covers the prerequisites of the courses available.

Read more

**
rather than
**

This course is much more focused on the meaning and usefulness of these things, rather than just learning how to do the maths.

The particular highlights are the use of geometric perspectives to give intuition rather than just labouring through the mathematics.

Great Course, exceptional in every way, gives you practice drill down some of the concepts, and handy programming assignments that are fun to work with, while not a complete refresher the course is good enough to grasp essence of linear algebra to build intuitive math, rather than classical way of teaching.

Thus the course should be considered a brief glance at linear algebra, rather than a proper course on the subject.

Focused on the geometrical view to look at the linear algebra rather than hand-calculations.

Read more

**
matrices and vectors
**

This course changed the view I look at matrices and vectors.

Mainly explains how to operate with matrices and vectors.

Great lectures and wonderful scrutiny of matrices and vectors.

It finally starts making sense why we use matrices and vectors.

Read more

## Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Research Scientist-Machine Learning $55k

Cloud Architect - Azure / Machine Learning $75k

Watson Machine Learning Engineer $81k

Machine Learning Software Developer $103k

Software Engineer (Machine Learning) $116k

Applied Scientist, Machine Learning $130k

Autonomy and Machine Learning Solutions Architect $131k

Applied Scientist - Machine Learning -... $136k

RESEARCH SCIENTIST (MACHINE LEARNING) $147k

Machine Learning Engineer 2 $161k

Machine Learning Scientist Manager $170k

Machine Learning Scientist, Personalization $213k

## Write a review

Your opinion matters. Tell us what you think.

##### Please login to leave a review

Rating | 4.5★ based on 466 ratings |
---|---|

Length | 6 weeks |

Effort | 5 weeks of study, 2-5 hours/week |

Starts | Oct 12 (last week) |

Cost | $49 |

From | Imperial College London via Coursera |

Instructors | David Dye, Samuel J. Cooper, A. Freddie Page |

Download Videos | On all desktop and mobile devices |

Language | English |

Subjects | Data Science Programming Mathematics |

Tags | Data Science Machine Learning Math And Logic |

## Similar Courses

Sorted by relevance

## Like this course?

Here's what to do next:

- Save this course for later
- Get
__more details__from the course provider - Enroll in this course