# Mathematics for Machine Learning

## PCA

**Mathematics for Machine Learning,**

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Rating | 3.3★ based on 140 ratings |
---|---|

Length | 5 weeks |

Effort | 4 weeks of study, 4-6 hours/week |

Starts | Oct 12 (last week) |

Cost | $69 |

From | Imperial College London via Coursera |

Instructors | Marc P. Deisenroth, Marc Peter Deisenroth |

Download Videos | On all desktop and mobile devices |

Language | English |

Subjects | Data Science Programming Mathematics |

Tags | Data Science Machine Learning Math And Logic |

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## What people are saying

**
programming assignments
**

Programming assignments are really difficult and at many points frustrating.

Even though the instructor seems immensely knowledgeable he could work on delivering the material (which is more abstract than before to his credit) in a clearer manner.The programming assignments are great albeit a bit hard to troubleshoot at times.

You are then given programming assignments where at least half the effort is to try to understand what is being asked before you start to work to implement it.

There are some issues with the programming assignments and the lectures could do with some more practical examples.

I feel that the programming assignments were a bit more challenging and sometimes I was not too sure of what I was doing.

Programming assignments are a little difficult.

Programming assignments' quality is too bad to follow it.

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**
machine learning
**

Very hard to follow, but you need to do it to understand machine learning very well.

I'm giving it only three stars because this is not what I expected, I signed up for this track to gain additional conceptual overview of how maths in many machine learning applications works on high level.

It was challenging but worth it to enhance the mathematic skills for machine learning.

Great capstone for the three-class Mathematics for Machine Learning series.

However, it just like the ingredients the math for machine learning will not be complete without attempting to this one.

its a good course to learn mathematics essential for machine learning This course demystifies the Principal Components Analysis through practical implementation.

That's a great online courses can help people have enough background to break into Machine Learning or Data science concise and to the point.

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**
first two courses
**

This is not the case for the first two courses of this specialisation.

The first two courses in the Mathematics for Machine Learning specialisation are excellent - even amongst the best online or traditional maths courses I have taken.

This course brings together many of the concepts from the first two courses of the specialization.

Far more challenging than the first two courses.

This course does require you to have some prior experience, though, so if you are new to programming or linear algebra (not just the concepts but how to apply them) it's bets to take the first two courses with some additional help (maybe Khan academy or even MIT OCW.

Like the first two courses of the specialization, this course is shallow, shouldn't be anyone's introduction to the subject and is a refresher at best.

I've finished all the two previous courses in this specialization.I was shocked at seeing the content and programming assignments given to us.It was totally different.They expect a lot from us.Content is not up to the mark.First two courses was awesome.But this course is an exact opposite to the first two.Totally disappointed!!

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**
previous courses
**

The previous courses were great at guiding, and in large part spoon feeding.

Unfortunately this course does is of much lower quality than the previous courses of the specialization.

This course is way more brutal than the two previous courses in the specializationIt is also very mathematically oriented, it lacks the graphics / animation / intuition that was given in the first two courses.However, if you make it, you indeed have a good understanding of PCA.

After taking/passing the two previous courses, this course is very disappointing.

I passed both of the previous courses.

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## Careers

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

Foundations Instructor $47k

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Financial Foundations Specialist 3 $53k

Instructor of Social Foundations of Education $62k

Mathematical Statisticians $74k

Prof and Head, Mathematical Sciences $82k

MATHEMATICAL STATISTICIAN EAS $82k

Adjunct Professor - Foundations (Art) $83k

Foundations Level Programmer $93k

Chair, Department of Mathematical and Statistical Sciences $120k

Senior Mathematical Statistician $123k

## Write a review

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Rating | 3.3★ based on 140 ratings |
---|---|

Length | 5 weeks |

Effort | 4 weeks of study, 4-6 hours/week |

Starts | Oct 12 (last week) |

Cost | $69 |

From | Imperial College London via Coursera |

Instructors | Marc P. Deisenroth, Marc Peter Deisenroth |

Download Videos | On all desktop and mobile devices |

Language | English |

Subjects | Data Science Programming Mathematics |

Tags | Data Science Machine Learning Math And Logic |

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