Voltar para Mathematics for Machine Learning: Multivariate Calculus

estrelas

4,863 classificações

•

870 avaliações

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. We then start to build up a set of tools for making calculus easier and faster. Next, we learn how to calculate vectors that point up hill on multidimensional surfaces and even put this into action using an interactive game. We take a look at how we can use calculus to build approximations to functions, as well as helping us to quantify how accurate we should expect those approximations to be. We also spend some time talking about where calculus comes up in the training of neural networks, before finally showing you how it is applied in linear regression models. This course is intended to offer an intuitive understanding of calculus, as well as the language necessary to look concepts up yourselves when you get stuck. Hopefully, without going into too much detail, you’ll still come away with the confidence to dive into some more focused machine learning courses in future....

DP

25 de Nov de 2018

Great course to develop some understanding and intuition about the basic concepts used in optimization. Last 2 weeks were a bit on a lower level of quality then the rest in my opinion but still great.

SS

3 de Ago de 2019

Very Well Explained. Good content and great explanation of content. Complex topics are also covered in very easy way. Very Helpful for learning much more complex topics for Machine Learning in future.

Filtrar por:

por Salem A

•20 de Jun de 2020

If you do not have a background in programming, some of the assignments will be intimidating and hard to do but if you go over it sequentially you will get the hang of it but it will take you time to do so. The lectures are too short and I feel that some concepts were not clarified enough because of how fast the lecturers go over them. The course, in general, is good for having an overview of the material so do not expect to cover these topics deeply. The presentation and the way some concepts were tough were enjoyable and enriching.

por Fang Z

•11 de Jul de 2019

I really love Samuel's teaching style. He strived to make people understood by showing a lot of graph and I can easily follow him step by step. However, David's teaching I couldn't follow up his mind much maybe because less explanations given during the lecture.

In addition, I found some quiz have huge amount of calculated amount which I really spent a lot time to verify the answer.

Finally, I hope more detailed explanations could be given if I made mistakes in some quiz so I could boost what I've learned so far.

Thanks,

Fang

por Hermes J D R P

•28 de Fev de 2020

The first 4 weeks of the course were amazing: great content, clear explanations and fair and interactive assessment activities. However, the last 2 weeks weren't as good as the previous ones. That's why I don't give this course 5 stars. By and large, the first two courses of this specialization are the best resources available on the internet to learn the foundations of mathematics for Machine Learning. I recommend that instead of doing the last course, you had better try to read the related book wrote by Deisenroth.

por Christiano d S

•3 de Ago de 2020

this course contains good lessons, and the level of assignments is proportional to what is being taught. there are some minor issues at some of the videos, but it´s possible to clear the doubts in foruns, in general, I´ve found this course the best one by far compared to other courses in coursera in which you have to spend a lot of time searching for extra information and content to accomplish the assignments. for the first time I felt the instructors actually taught the content.

por Sergio A G

•21 de Out de 2020

It starts brilliantly, but the last 2 weeks are quite bad. It has nothing to do with the new teacher taking over that part, I think he is as good as the other one. It's a matter of goals and focus. It seems like everything you learn in those weeks are just random things and little 'magic tricks', it's hard to see why they're relevant to the subject and everything seems disconnected.

Still, I really enjoyed the first 4 weeks. Awesome content, they made me realize I love calculus.

por Wu X

•21 de Abr de 2020

This course teaches multivariate calculus and its applications. In particular, Jacobian and Hessian Matrix are introduced as Matrix versioned derivatives (first order and second order), along with gradient descent optimization based on them. The structure of the course is a little bit loose, so it's not a good choice for those who want to seek systemically arranged learning materials. But it still worth taking for a better perspective and ideas.

por Saras A

•29 de Jan de 2020

Good course. I wish it had more sections as in a total of 12 sections or weeks and more steps to gain a more thorough graphical understanding (and perhaps even a more mathematical/algebraic understanding however overall that's much easier for me on that front...).

From a Data Science or Machine Learning perspective Week 6 (linear regression and non linear regression with chi-squared methods etc) were the most interesting.

por Donna D C

•25 de Abr de 2020

Nice balance between rigor and developing intuition (again as in the previous linear algebra course in this series). I would’ve liked some “homework” reading about backpropagation for training the simple neural to prepare for the future courses. Also, more references for additional reading on least squares minimization techniques to tie more into the statistics underlying the techniques. I love the stuff, thank you!!

por habib k

•29 de Ago de 2021

This course gives a great intuition about the calculus required for machine learning. Meanwhile the lecturers do not explain some concepts completely which is really bothering. In those situations always check the forum because you are not alone and other students probably had the same problem and someone would have explained it in more details or posted a link to a video that explains that concept in more details.

por Dan L

•30 de Mar de 2019

The course accomplishes its goal of connecting concepts in calculus to machine learning, and is appropriately paced for students who have covered calculus in the past and are seeking a refresher or deeper understanding of its applications to real-world problems. For those who don't already have a certain minimum familiarity with the mathematics, however, the course will probably move at too fast a pace.

por Matt P

•19 de Jul de 2018

Great class - very informative and eye opening - even with quite a bit of linear algebra background. Really liked the eigenvector and eigenvalue section - great descriptions. I wish the neural network discussion went on a bit further. I found some of the programming assignments' instructions a bit vague and confusing - what should have taken a few minutes ends up taking a half hour.

por Aneev D

•19 de Out de 2018

This course is great in the sheer efficiency with which it goes through the content required to prepare you for machine learning. It builds an intuition for what's going on, which is amazing. Some parts are confusing, and I recommend looking at Khan Academy for the lectures on Jacobians and steepest ascent, and 3Blue1Brown for feedforward neural networks.

por Wenyuan Z

•10 de Jan de 2019

Well the course is generally good, the only problem is that David sometimes may just skip the process and lack more explanation when performing the calculation, it's easy to lose track of what he is calculating if not reviewing the video over and over again, but anyway, the whole class is worth recommendation, thank you for your teaching, professors

por Walter S

•3 de Fev de 2021

This is a good calculus refresher and exploration of optimization processes and techniques. It goes rather fast and if you are rusty on the concepts you will need help from other sources such as Khan academy. I would have liked hands-on examples of using the functions in python libraries and matlab, as this was just a footnote on the last lecture.

por Anton K

•18 de Set de 2020

It was exciting at some points. However, I left the course with the feeling that some subjects were not covered properly. The technical aspect of the course (e.g. video quality, visualizations, practice with python) were really great, lots of interesting and new teaching methods (at least for me). I wish this course was longer and more detailed.

por Mihai R F

•1 de Nov de 2019

Very valuable training course from the insight/intuition point of view. This is more of an overview of the calculus for machine learning giving the student a good direction of what to study and where to start from. I think that actually mastering the subject will require extensive additional exercises from other sources

por Dmytro B

•11 de Fev de 2019

Very helpful to review and get introduced to mathematical concepts behind machine learning. There is a fair bit of practical exercises as well. The only thing I am less happy about this cousre was a lack of additional suporting materials and references to other resources to help gain more knowledge on the subject.

por Gerard G I R

•11 de Mai de 2020

I had no previous experience with multivariate calculus. This was a nice introduction to the topic, but in my opinion it does not allow me to say that "I know" multivariate calculus. Nevertheless, I think it is work taking as an introduction before going to more complete courses in multivariate calculus.

por Luis M V F

•16 de Mar de 2019

I think Samuel Cooper is an amazing instructor. However, the last two weeks taught by David Dye were very difficult to follow. I think David should improve his explanations because I did not enjoy too much his course on linear algebra, and this course was great until he started with the last two weeks.

por Christian G S

•17 de Abr de 2021

Very solid introduction into Calculus. Keep in mind that this is a course meant to give you an intuition and basic understanding. Sometimes there are small gaps in the curriculum to the quiz (but you will easily be able to make up for them by just reading the according Wikipedia page). Was a pleasure.

por Abhirup B

•30 de Ago de 2020

exercise and programming assignments are good ....and i can grow a sound concepts after completeing them.lectures are also good ...but some lecatures are too quick and a little elaboratiion in some places would have been helpful(particularly those in the last couple of lectures)

por Kevin E

•15 de Jun de 2020

Excellent course. It covers so much without making me feel overwhelmed. I would like to see more hands-on demonstration on linear and non-linear regression, but I was able to complete the quizzes and assignments. This without any previous multivariate calculus instruction.

por Divyang S

•8 de Ago de 2020

Overall a good course to give us a better idea of what sort of math is used in ML. But I feel they went too fast in this course, so I personally lagged a bit in understanding certain crucial concepts. Also, it'd be much help if the instructors could mention reference books.

por Michelle W

•17 de Nov de 2019

I would say this entire series is better advertised as a quick *review* of the pertinent concepts. Otherwise, someone with no background in the topics covered may struggle (unless they are particularly talented with quickly learning new mathematical concepts).

por Shintya R R M

•6 de Mar de 2021

This course is good to start learning Machine Learning. There are also labs practice so that I can acquire deeper understanding by the visualization. However, some materials are not explained clearly, such as Newton-Raphson method and Lagrange Multiplier.

- Analista de dados do Google
- Gestão de projetos no Google
- Design de UX no Google
- Suporte de TI do Google
- Ciência de dados da IBM
- Analista de dados da IBM
- Análise de dados da IBM com Excel e R
- Analista de Cibersegurança da IBM
- Marketing em mídias sociais do Facebook
- Desenvolvedor de nuvem full stack – IBM
- Representante de desenvolvimento de vendas da Salesforce
- Operações de vendas da Salesforce
- Suporte de tecnologias da informação do Google
- Certificado profissional de suporte em TI do Google
- Automação da TI do Google com Python
- DeepLearning.AI no TensorFlow
- Certificações populares de segurança cibernética
- Certificações populares de SQL
- Certificações populares de TI
- Ver todos os certificados

- cursos gratuitos
- Aprenda um idioma
- pythonpython
- Java
- web designweb design
- SQL
- Cursos grátis
- Microsoft Excel
- Gestão de projetos
- Segurança cibernéticaSegurança Cibernética
- Recursos humanos
- Cursos gratuitos de ciência de dados
- falar inglês
- Redação de conteúdo
- Desenvolvimento Web completoDesenvolvimento Web Completo
- Inteligência artificial
- Programação em C
- Habilidades de comunicação
- Blockchain
- Veja todos os cursos

- Competências para equipes de ciência de dados
- Tomada de Decisões Baseada em Dados
- Habilidades de engenharia de software
- Habilidades Pessoais para Equipes de Engenharia
- Habilidades Administrativas
- Habilidades de marketing
- Habilidades para Equipes de Vendas
- Habilidades de Gerente de Produto
- Habilidades Financeiras
- Projetos de desenvolvimento de Android
- Projetos em TensorFlow e Keras
- Python para todosPython para todos
- Aprendizagem profunda
- Habilidades em Excel para negócios
- Fundamentos de negóciosFundamentos dos Negócios
- Aprendizagem Automática
- Fundamentos da AWS
- Fundamentos de engenharia de dados
- Competências de análise de dados
- Habilidades para designers de UX

- Certificados MasterTrack®
- Certificados profissionais
- Certificados universitários
- Graduações em negócios e MBA
- Graduações em Ciência de Dados
- Graduações em Ciência da Computação
- Graduações em análise de dados
- Graduações em Saúde Pública
- Graduações em ciências sociais
- Graduações em gestão
- Graduações nas melhores universidades europeias
- Mestrados
- Bacharelados
- Graduações com uma trajetória de desempenho
- Cursos em Ciências (BSc)
- O que é uma licenciatura?
- Quanto tempo leva um mestrado?
- Um MBA on-line vale a pena?
- 7 maneiras de pagar pela pós-graduação
- Ver todos os graus