Mathematics for Machine Learning

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Below are the top discussions from Reddit that mention this online Coursera specialization from Imperial College London.

For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to h...

Eigenvalues And Eigenvectors Principal Component Analysis (PCA) Multivariable Calculus Linear Algebra Basis (Linear Algebra) Transformation Matrix Linear Regression Vector Calculus Gradient Descent Dimensionality Reduction Python Programming

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Taught by
David Dye
Professor of Metallurgy
and 3 more instructors

Offered by
Imperial College London

This specialization includes these 3 courses.

Reddit Posts and Comments

2 posts • 97 mentions • top 70 shown below

r/learnmachinelearning • post
27 points • _SleepyOwl
Anyone taken Mathematics for Machine Learning Specialization by Imperial London College on Coursera?

Hi all,

I'm thinking about auditing the Mathematics for Machine Specialization by Imperial London College. Does anyone have experience with this course/professors/college? I think it's relatively new, but I see that others have been in it for the past month or so (maybe as beta testers?). Either way, if anyone has experience with it, I'd love to hear if it's worthwhile.

I'll update as I go through the course as well.

Mathematics for Machine Learning

r/learnmachinelearning • post
16 points • DarkBahamutBot
I want to get started on machine learning, but I have some doubts about the prerequisites

Basically, I want to learn enough to get a "feel" of how its like to develop in the area, to see if thats what I want to specialize myself in. I searched around for a bit and saw that some of the prerequisites for understanding machine learning are linear algebra and multivariate calculus. Because of that I was thinking of enrolling myself in this specialization in coursera:

https://www.coursera.org/specializations/mathematics-machine-learning

But I am not sure exactly if thats enough, and thats what I would like to know here. However, if its not, I would like to know what else I would need to learn regarding these specific fields, keeping in mind that I am not trying to become a researcher or anything of the sort, rather I am just exploring the area. Thanks in advance.

r/MachineLearning • comment
7 points • atulkum

There is https://www.coursera.org/specializations/mathematics-machine-learning course series on coursera. If that is too basic for you then read the book 'all of statistics' from Larry Wasserman and do all the problems in the book.

r/UofT • comment
5 points • kainu2612

Also if you just want to learn the basic math, without any difficulty of the math specialist or the math major, coursera has enough for you, no need to bother to learn from mat223/224

https://www.coursera.org/specializations/mathematics-machine-learning

r/MLQuestions • post
10 points • jimbob1141
Best resource/course to learn machine learning maths?

So I'm doing a machine learning course, and it shows me the algorithms, I have a rough idea of why it works but I want to understand on a better level than knowing when to use it. Is there a comprehensive course that teaches the maths more in depth? I was looking as "Mathematics for machine learning specialization" on Coursera. Have any of you guys taken this course?

https://www.coursera.org/specializations/mathematics-machine-learning?action=enroll#pricing

r/learnmachinelearning • comment
9 points • nom-de-reddit

Coursera has a couple of classes that might help...

https://www.coursera.org/learn/datasciencemathskills

https://www.coursera.org/specializations/mathematics-machine-learning

r/learnmachinelearning • post
19 points • EduGuy33
2 Maths Courses for Machine Learning Students

If you need to brush up on the key mathematical concepts, this might be for you.

First one is from Microsoft and covers Algebra, Calculus, Statistics, etc.. It's free to learn on the Edx platform: https://www.edx.org/course/essential-mathematics-for-artificial-intelligence

The second course is actually a series of 3 courses on Coursera (Imperial College London): https://www.coursera.org/specializations/mathematics-machine-learning Also covers all the key concepts but more in-depth. (If you take the courses individually, you can audit them for free.)

r/bprogramming • post
3 points • bprogramming
Course: Mathematics for machine learning
r/datascience • comment
3 points • Bayes_the_Lord

https://www.coursera.org/specializations/mathematics-machine-learning

r/datascience • comment
3 points • crypto_ha

If you prefer being spoonfed then choose the coursework/non-thesis option. If you have 3 months before the program starts, you should do Mathematics for Machine Learning Specialization on Coursera to refresh your math. After this, you’re all set!

r/learnmachinelearning • comment
3 points • ScotchMonk

Mathematics for Machine Learning | Imperial College London https://www.coursera.org/specializations/mathematics-machine-learning

r/greece • comment
6 points • onetwosex

Απειροστικό λογισμό (Calculus), γραμμική άλγεβρα (Linear Algebra), πιθανότητες/στατιστική (Probability theory & Statistics).

Υπάρχει και σχετική ειδίκευση στο Coursera, αλλά από ότι βλέπω δεν σου δείχνει καθόλου πιθανότητες:

https://www.coursera.org/specializations/mathematics-machine-learning

r/compsci • comment
2 points • sch77

You might wanna try this: Mathematics for Machine Learning Specialization

Mathematics for Machine Learning. Learn about the prerequisite mathematics for applications in data science and machine learning

r/datascience • comment
2 points • Bayes_the_Lord

I really need to refresh my calc so I'm about to start this: https://www.coursera.org/specializations/mathematics-machine-learning

Edit: If anyone has a better suggestion feel free to link me to it.

r/brasil • comment
2 points • soldcron

No Brasil eu ainda não tive contato com pessoas de humanas trabalhando com DS. O que eu sei é que no US tem muita gente migrando pra essa área, e muitos fazendo sucesso.

Eu respondi pra outra pessoa que interdisciplinaridade é sempre maravilhosa. Nesse caso eu considero mais ainda, dado que leis de proteção aos dados estão surgindo em muitos países (incluindo aqui).

Não acho que seja necessário uma formação técnica, desde que você tivesse conhecimento nos tópicos básicos da área.

No seu caso, aconselho começar relembrando matemática do ensino médio. Depois pega esse curso aqui:

https://www.coursera.org/specializations/mathematics-machine-learning

Pra você não desmotivar, vai fazendo em paralelo os cursos da Alura. É uma ótima porta de entrada.

Depois disso provavelmente você já vai ter uma base pra saber sozinho onde atacar. Na dúvida, consulte os livros que deixei no post. Eles são ótimos materiais de consulta, além de serem ótimos guias.

r/OMSCS • comment
2 points • bardsmanship

There's also a Coursera specialization by the authors of the book, but I think you're better off with the book because the courses are far too short and easy.

r/artificial • comment
8 points • iTeush

For machine learning in Python and R: https://www.udemy.com/machinelearning/ And after if you're interested in deep learning: https://www.udemy.com/deeplearning/ Andrew ng course is very interesting for the theory behind the algorithms, if you need to train yourself in mathematics you can also follow this course: https://www.coursera.org/specializations/mathematics-machine-learning

r/learnprogramming • comment
5 points • ChemiKyle

The only path to getting good at something is practicing it! It helps to start with smaller things and explore around, so a bit of spreading yourself thin at first isn't a waste of time at all!

The first time I launched a webapp I did the whole nine and built it from the ground up on a LAMP stack - way more difficult than it needed to be. Since you're just practicing and playing around, there's no need to worry too much about backend and hosting, so an easy start on web stuff in Python is Flask and learn the rest from there. The last thing I built used that and it was far easier, I had workable prototypes in a couple days and was able to iterate more easily from there.

Coursera has some classes on ML mathematics that utilize Python as well! Kaggle stuff - I think - can wait until you feel more comfortable with what's going on. Since you're a "first principles" kind of learner (me too!) it'll probably feel better to build up from basics rather than backtrack from frameworks.

r/datascience • post
1 points • HannahHumphreys
Mathematics for Machine Learning | Coursera
r/learnprogramming • comment
1 points • Skirkyn

I did one course from this https://www.coursera.org/specializations/mathematics-machine-learning specialization. Was pure linear algebra and python coding. They cover matrices transformation in space pretty good as well as operations on vectors. Pretty intense though. I have an applied math degree but still wasn’t relaxed. Buts that’s a good thing. Don’t know what’s there next. Calculus on Coursera is free and not too bad as well.

r/OMSCS • comment
1 points • teapink

Check this course out — https://www.coursera.org/specializations/mathematics-machine-learning .

r/coursera • comment
1 points • ultimatt42

Stolen content: https://www.coursera.org/specializations/mathematics-machine-learning

r/learnmachinelearning • comment
1 points • arkady_red

Definitely not difficult (though I do wonder what's their deal with Abelian groups, uh). However, if to find them hard, you may have a look at the Coursera specialization and ask questions on the forum. I'm not sure that's worth the time investment (I'd rather follow the 2 fast.ai courses), but YMMV.

r/learnmachinelearning • comment
1 points • abs51295

https://www.coursera.org/specializations/mathematics-machine-learning

How about this?

r/learnmachinelearning • comment
1 points • sch77
r/learnmachinelearning • comment
1 points • thevastandthecurious

Imperial has a great Coursera specialization on Mathematics for Machine Learning. Highly recommended!

r/learnmachinelearning • comment
1 points • shreddit47

Other than my stats text books no, lol but a great crash course I took was on Coursera. From AMII school called “Intro to Applied Machine Learning”. It gives a great intro to the type of math you’ll need without getting too complicated. If you want something a little more technical and complicated, imperial college has a good program on just the math on Coursera. Link: https://www.coursera.org/specializations/mathematics-machine-learning. Another program I did was the IBM data science professional cert. touched on a bunch of different things from the math to coding it in Python. It was a great crash course but wasn’t a big fan tbh. I’d start with AMII and Imperial college. In that order. People say Stanford has a very good course/program on Coursera. I plan to take that next. Andrew Ng put it together. Basically, if you’ve taken a few stats courses, linear algebra, multivariate calculus, this stuff will be a refresher for you.

r/ArtificialInteligence • comment
1 points • ulysses_black

You might like to check out the specialization offered by the Imperial College on Coursera. It is free to audit the courses and covers all the subjects required for data science. https://www.coursera.org/specializations/mathematics-machine-learning

r/learnmachinelearning • comment
1 points • pontstreeter

I’m halfway through this Imperial College course (on Coursera) called Mathematics for Machine Learning and found it to be very useful. The Linear Algebra part is very good and so is the second part multi variate calculus. Haven’t started the third part on PCA yet. https://www.coursera.org/specializations/mathematics-machine-learning

r/OMSCS • comment
1 points • Aleriya

I'd recommend being familiar with matrices and matrix math. Coursera has a nice series that gives a solid foundation if you are interested in ML coursework: Math for Machine Learning

r/learnmachinelearning • comment
1 points • ml_kid

> Not much math in the life of ML engineer. Their main task is to implement ideas of others into actual working, scalable code.

I want to be an ML engineer. I have finished Coursera Course and now planning to do Deep Learning AI course. And also this specialization - Mathematics for Machine Learning, would that be enough to make a career switch? (currently I work as a backend dev)

r/OMSA • comment
1 points • nmac1818

This one might be worth looking into as well:

https://www.coursera.org/specializations/mathematics-machine-learning

r/programming • comment
1 points • Nicksil

This user spams their linksynergy redirecting referral links all over.

For those genuinely interested in seeing what's behind the curtain, here's a direct link to the content:

https://www.coursera.org/specializations/mathematics-machine-learning

r/programming • comment
1 points • TheLastLived

Here you go mate https://www.coursera.org/specializations/mathematics-machine-learning

r/learnmachinelearning • comment
1 points • hisham32

A complementary resource with 3blue1brown videos would be the Coursera course Mathematics for Machine Learning by Imperial College London.

r/OMSA • comment
1 points • DangerousBiscotti6

I am in the same boat. I did the Introduction to Computer with Python from GTx (edX) and I am currently doing the Machine Learning Core from Microsoft (edX). Everybody also suggests the math course from Imperial College (https://www.coursera.org/specializations/mathematics-machine-learning) so I am doing that one too. For programming itself I would stay away from Data Camp. It is better to learn how to use the language for data analysis. I am in the DC area too and would be interested in forming an study group.

r/learnmachinelearning • comment
1 points • kaiNbleu

You can check out Coursera's Mathematics for Machine Learning Specialization. I haven't done the specialization but have gone through few videos from it's Linear Algebra course on YouTube and it was good.

r/OMSA • post
1 points • Menino80
Is taking four classes in a semester feasible? Will not be working, pretty good R background

Hi all,

I'm entering in the fall and am planning on quitting my current job and just taking the semester off to study (the job was a bust and have been wanting to leave for a while)

I have an MBA and about 2 years working pretty often with R, altho it's mostly dplyr and haven't done a lot of stats, but even so I know the syntax and generally know my way around the program. My math isn't great and I'm definitely boning up on Linear Algebra right now, taking the Coursera Math For Machine Learning course to prepare.

​

If I get most of the way through that by mid August, would I be ok taking CSE 6040, IYSE 6501, CSE 6242 AND MGT 6203? As I said I already have an MBA and about 3.5 years of overall experience in various data roles of varying complexity, so I feel like I have most of the background I need. I'm just worried about the end of 6040 as I heard it's got the most linear algebra. But if I finish my class by August, I should be good right? It's a lot of classes but I'd like to get a good base of knowledge so I can find another job early next year.

​

I feel like these four classes have the least "Machine Learning" content and even if it does, that's what I'm here to learn. Just wondering if the combo of being new to some of the math would make this courseload too much.

r/OMSCS • comment
2 points • StatsML

I highly recommend Mathematics for Machine Learning from Imperial College London:

https://www.coursera.org/specializations/mathematics-machine-learning?

It's among the most concise ways to get the linear algebra and calculus you'll need that I've seen. Doing the first two courses should give enough background for ML, AI, and (probably) DL.

A motivated and mathematically inclined student could finish those in 2-3 weeks total. Maybe 4-6 if the material is new to someone.

The other math piece that's needed for these types of courses is probability. I don't think it's unreasonable to consider these things prerequisites without offering a course in them.

If I were to lobby for another OMSCS ML course (other than the aforementioned DL), it would be CS 7545, Machine Learning Theory.

r/OSUOnlineCS • comment
2 points • Matsukaze

Look into the Mathematics for Machine Learning Specialization by Imperial College London on Coursera, which covers some of the math you may need. Imperial College London is also going to be offering an online master's program in machine learning through Coursera.

Also see deeplearning.ai, which has a Coursera specialization on deep learning.

r/WGU_CompSci • comment
2 points • tjscollins

Although I took Linear Algebra and multi-variate calc many years ago, I plan on doing this before applying to OMSCS: https://www.coursera.org/specializations/mathematics-machine-learning and https://www.coursera.org/specializations/statistics

r/MachineLearning • comment
2 points • david_s_rosenberg

I don't know anybody who has taken it, but this looks promising from the description: https://www.coursera.org/specializations/mathematics-machine-learning

r/learndatascience • comment
1 points • keplaxo

I’ve found both of these useful.

Khan academy : Statistics and probability

Coursera Specialization :Mathematics for Machine Learning Specialization

r/learnmachinelearning • comment
1 points • ronnyma
r/learnmachinelearning • comment
1 points • Mazziatore

Greetings!

https://www.coursera.org/specializations/mathematics-machine-learning

I have not taken this course yet but looking at the syllabus I believe it has most of what you're asking for, and you can practice python at the same time.

You may need to take another course for more advanced statistics stuff though (like distributions for example).

r/learnmachinelearning • comment
1 points • sch77

It might help Mathematics for Machine Learning https://www.coursera.org/specializations/mathematics-machine-learning

r/datascience • comment
1 points • DelverOfSeacrest

If you want to learn a few neat tricks in Python, just read the documentation for the common data science libraries (Numpy, Pandas, Scipy, scikit-learn, Seaborn, Matplotlib). They are very well-documented and come with quick tutorials. That would teach you more about them than any of those courses ever would.

In terms of machine learning, I'd stay stay away from Coursera and Udemy and pick up a book. They are both meant to appeal to a general audience which means they leave out the math side of things and you don't fully get a sense of what goes on in these ML algorithms. Here's an example of how watered down these Coursera courses are:

Here is a Coursera specialization in Math for Machine Learning

Here is a book written by the same exact people with the same premise. Notice how much more in depth the book goes. It gives you a far better understanding of how math relates to machine learning and covers many more interesting topics.

It isn't just them though. All of these courses do it. If you're comfortable with math/stats, I'd definitely pick up a book.

r/learnmachinelearning • comment
1 points • stochastaclysm

Coursera have one. But basically it’s linear algebra, probability and statistics, and calculus.

https://towardsdatascience.com/the-mathematics-of-machine-learning-894f046c568

https://www.coursera.org/specializations/mathematics-machine-learning

r/learnmachinelearning • comment
1 points • mallasahaj

I will be studying maths now. So I enrolled in Coursera's Mathematics for Machine Learning https://www.coursera.org/specializations/mathematics-machine-learning. I have some knowledge about the maths from my A levels. Enrolling in this course to get a certificate. I'll also be looking into Khan Academy for maths. So let's see how things go. Wish me luck!!