Math for Machine Learning by Imperial & Coursera: REVIEW

Lol, you have almost as many tabs open as me.

U sound like MarkGoldbridge....

I'm doing the first course and its the best math course I have ever seen. What a teacher!!

What I think is if you haven't done the math before I recommend to first cover Khan academy algebra, linear algebra and calculas playlist

Yes there are some challanging labs and programming assignment....but after clear understanding of concept I found easy to solve and the tip is if you exhausted dont do it.......do it with fresh mind.

Where are probabilities and statistics

for the third course it would be very good if they include the statistics and probability instead of PCA

Unfortunately, their teaching methodology is more like: How to draw an owl. Draw one little circle, Draw on big circle. DRAW THE F**KING OWL! ... not for beginners.

does this course help us with coding?

I am still in the second course, and you wouldn't believe me when If I told you that I already finished my Deep Learning specialization, but chose to study this specialization to gain more depth in the related math, and still I am impressed so far by the first 2 courses.

Does the first course teach enough linear algebra to be able to follow a university level ML course? I already know basic high school LA btw.

I finished the Deep Learning specialization and would like to take another course/specialization and use my Coursera for students credit on another course. Which of these two is better to put on a resume when applying for a DS/ML/DL job?

-Mathematics for Machine Learning (Imperial College London - this one)
-Modern Application Development with Python on AWS (Amazon Web Services)

I took part in a hackathon, where we used AWS, so I guess some cloud-based experience would be useful in an industry setting, that's why I am considering that specialization.

thank you for your reviews. really I was confused about this course

thanks for the review, but I thought they should have added the Statistics and Probability course as well. I am designing syllabus for Mathematics for Machine Learning for my master's students. I think this is the course which I will consider.

does anyone have the notes for the specialization

would you advise to begin with python ? or html / css / JS ?

Sounds very compelling

That's what i looking for some time ago. Thanks so much for the info Giles.

I am was not strong, when it came to maths at school but in in my "post-high school" education, I worked really hard and exceeded expectations. So much so, that my parents asked if I had cheated or paid someone to write my exams, lol...but this gave me the belief to overcome these fears I had, related to these "high school" shortcomings and changed my perception that DS, ML and AI were realms for other people, not me..... I have become really interested in these fields, ML and AI in particular. I am a long way from reaching my goals but your channel and recommendation are useful, awesome, insightful and inspiring. PS: His new courses starts today and I just watched this vid! 5th July 2021 - Thank You so much.

is it availbale on udemy?

I am scanning through skills required for ML, very helpful indeed, at least I know I will be able to do maths ;)

Thank you for this recommendation, Giles. I just completed the entire course. tl;dr: I'm glad I did it, it's a great course overall and I would recommend people take it, bu unlike you, the reason I also found the PCA course (i.e. the third and last part) the weakest isn't because the teacher wasn't as personable as the previous two. For those interested, read below for my full impressions of that part:

I didn't really mind the fact that the third teacher doesn't really connect with the viewer. Yes, they don't smile much and they don't have the same kind of energy as the first two teachers, but as long as the pedagogy is there, it's all good... But that's the issue really: the teacher and the content make too many assumptions about the students, and the pedagogy felt lacking as a result.

Even if the course is labeled "intermediate", it's supposed to be the logical progression of courses 1 and 2, and it feels like anything but that. Mathematical concepts, formulas and notation are often glossed over in a sentence, with few visual or concrete examples, such that you're very quickly overwhelmed if your math knowledge isn't already way beyond what was expected in the other two courses. When you're not already really comfortable with (from my point of view) fairly advanced maths, too much abstraction can be very intimidating and a complete motivation killer. You just end up feeling like you're an idiot or like mathematics just aren't for you.

The course content is lighter (4 weeks only), yet at the same time, it covers far more complex topics, and it often feels like much less effort was put into it. For example, the teacher often defaults to giving you reading material - some of which is quite heavy on esoteric notation that is barely covered, if at all - instead of making explanatory videos. Another example: the feedback on quiz questions, most of the time, amounts to "Great job!" or "Incorrect", with no explanations. The quizzes themselves often feel completely disconnected from the lessons that precede or follow them. They can be extremely easy, or extremely hard, usually with no in-between. And the programming assignments can be strangely worded or contain mistakes at times, which can throw you off as a student. They certainly threw me off, even though I'm already quite familiar with Python and numpy. In other words, the substance of the assignments wasn't necessarily insurmountable - I was shocked how quickly I completed some of them, in fact -, but the way they're framed and explained made some of them more puzzling than they needed to be sometimes. All those aspects are big departures from the teaching style of the previous courses. Lastly, though this was also an issue with the other courses, the teachers and staff barely ever reply to questions on the forum. Not too much of an issue when the course itself is great, but for this third course, it didn't help matters.

I realize I sound very critical, but again, this isn't to say people shouldn't take the course. They should take it, including the third part, if they have any interest in machine/deep learning and they need to brush up on maths. It's easily worth the €40/month - by the way, you can go through the entire curriculum in a month if you can devote 4-6 hours to it almost every day like I inexplicably managed to do. I just wanted to push back a little against what you said in the video, where you seemed to imply that people were unfairly complaining about some of the assignments. From someone who isn't already very comfortable with maths and abstractions but was diligently making their way through all the content regardless, let me emphasize: it's not just that the third course will challenge you and you should just deal with it; it's that it could stand to be improved, or at least give more pointers to helpful external resources (not just a link to a Wikipedia article). Being challenging or intermediate level isn't an excuse for an unbalanced difficulty curve or hasty coverage of complex topics.

I will say this though: that last quiz before the final assignment forced me to do a deep dive on partial derivatives (especially the chain rule) and gave my poor little brain quite a workout. Genuinely thankful for that. And again, the previous two courses alone are worth enrolling for.

Looking forward to more course/book recommendations! :)

Actually I completed the first course of this specialization and having completed this far Idk why are people commenting that the assignments are hard. In fact those were totally based on lectures. After all this is the price you need to pay to learn something new and earn a certificate from a renowned institution. Otherwise just fast forwarding the lectures and solving just the petty assignment doesn't add any worth to your learning. Rather it is the best course for anyone who wants to equip themselves with the mathematical knowledge needed for machine learning.

I am not good at Mathematics. Where do I start to improve my maths?

I enrolled in this course when i could free because of my school account but i now i cant get a certificate without upgrading my account. So the question is if i add the course in my linkedin without the certificate when i completed the course does it matter that i don't have a certificate?

I love mathematics… I wish I were younger so I could become mathematician. Now I just work every day and come home ….

PCA is more complicated than computing eigenvectors or multivariable calculus. Although PCA is part of multivariable calculus.

is MatLab required for this?

+1

Can we audit this course for free without the certificate? Will all of the content be available if we audit it? Will the assignment problem solutions be available if we just audit the course?

i had started the course but couldn't find time due to work i would definitely pursue it, now that you recommend it

Well, thanks to this video I'm ready to re-learn math the right way.. thank you.

How did you gety past that first programming assignment in the PCA class? It was impossible........ It took me over 8 hours to do.

I am wondering why did they not include any course on probability and statistics in this specialization. I took these courses during my bachelor's in engineering but looking for a resource to revise the subjects. Is there any other specialization that includes a course on probability and statistics that you recommend?

introductory level courses

This course was really helpful!. It saved me in my first Master's degree semester.

This guy is into programming but has old school British mathematician vibes

Very useful review. Thank you.

the Maths for Machine Learning specialisation was one of the first that i've ever done on Coursera. and it's still my favourite set of courses i've done on Coursera so far.

Your justification for why the assignments weren't "too hard" was all the convincing I needed that this class is bad. If I have to spend extra time digging in more depth online then there is no point to take that course in the first place. I'll just save some time and go straight to the research online step. Why take a course where they don't teach you what you need to know?

Can you please say how it relates to the Mathematics for Machine Learning book, do you think the book is more comprehensive?

Any recomendations, books or courses for learning algorithms?

Better to take this before or after learning a bit of machine learning?

does this specialization cover all the requisite maths for ML though?

Geeze - warning about this video - be prepared to learn

What I was looking for. Ty

Please make review on applied ai course.🙏

excellent review, I would add that using/learning sympy in parallel helped me a lot following the course and understanding the mathematical concepts

Hey Giles. Thank you for the review. Is this course better than the free Mathematics for Machine learning book that you had suggested earlier on your channel? Is it worth to spend money on this specialization when that free book exists? I am asking since you had given a positive review about that book too.