Вернуться к Mathematics for Machine Learning: Multivariate Calculus

звезд

Оценки: 4,784

•

Рецензии: 852

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....

JT

12 нояб. 2018 г.

Excellent course. I completed this course with no prior knowledge of multivariate calculus and was successful nonetheless. It was challenging and extremely interesting, informative, and well designed.

DP

25 нояб. 2018 г.

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.

Фильтр по:

автор: Maksim U

•3 янв. 2019 г.

I did learn quite a lot throughout the course. The problem is that most of my knowledge came from elsewhere while the explanations by the course instructors were quite unclear till I referred to extra resources. At the same time, some other explanations were on the obvious side, so I'd say the instructions are kind of inconsistent in their difficulty. The real-life examples were relly good though. The same concerns the quizzes, some are absolutely great and intuitive, while the others just leave you puzzled about what you are even expected to do with no extra info offered when failed.

The course is kind of sloppier than the first one and the reviews say the third one is even worse, so I won't be doing it.

Finally, I cannot even complete the last graded assignment and get my certificate as well as some other learners because the thing just throws an error all the time. There is zero reaction from the crew that is supposed to be moderating the forums.

All in all, a fine "guideline" course. But do not expect to be presented much inside the course itself.

автор: Pritam D

•13 сент. 2020 г.

While the topics covered in the course are good, the depth and clarity with which each topic deserves to be explained, remains unfulfilled. The lectures are easy to understand, but sometimes you'll have to jump to other resources to get a better understanding of the topics covered. The difficulty of assignments is relatively very high, compared to their respective lectures.

Moreover, I feel that categorizing this course as a "beginner" course is somewhat questionable, as a complete beginner will face a lot of hurdles, given the number of new topics introduced in each lecture, the succeeding (often difficult) assignment, and the brevity of explanation. This course is more of an intermediate level, and some prior experience of Multivariate Calculus is required. I personally had glazed over Multivarious Calculus during my undergraduate, and even with that background, the difficulty seemed frustrating. For me, other resources, such as 3blue1brown youtube videos and Grant's KhanAcademy videos were necessary to complete the course.

автор: Leandro C F

•22 мар. 2021 г.

I've took the first course about linear algebra and it was brilliant. Unfortunately I did not have the same impression on this course.

The contents of the course is very important, but some topics were covered very quickly and superficially.

I also noticed that many people liked the first instructor, but for me the fact that he emphasizes one in every four words annoyed my learning experience. I spent more time paying attention in the emphasis than in the contents.

автор: Harsh D

•14 июня 2020 г.

After the first course of the series, I expected more out of this. Certainly, the course covers basics but there's a gap in between the weeks. May be it was done to ensure the course could be restricted to 6 weeks, but then again course 3 is just 4 weeks. Not sure what happened there, this one certainly requires restructuring.

For Imperial College: If you would like to know what I am talking about, please go through the discussion forums.

автор: Paul F

•10 мая 2020 г.

Towards the end, you see that the lecturers and the Team lost their motivation for a bit. Explanations are done very quickly and the exercises lack proper programming. The last one for example can't be passed if you write the functions in two different cells (as it is displayed in the workbook when you start), you need to copy them to one cell. This is really badly designed.

автор: Oliver K

•1 февр. 2020 г.

The first few weeks were a great introduction to derivatives, but the further it got the more the content seemed rushed and the exercises lazy. I will now go back and read secondary literature to really understand those parts, and not just calculate derivatives over and over. Samuel was a fantastic instructor though, kudos!

автор: Marcin

•12 авг. 2018 г.

It's one of the toughest things that I've done in my life. The content is really interesting and applicable, but at times you might get stuck with quizzes or assignments because there is not enough guidance given. All in all, I'd recommend this course to everyone working in analytics.

автор: Sam C

•17 апр. 2018 г.

A quick short introduction to multivariate calculus and few machine learning techniques, but without much detail mathematical proofs for some ideas. It's a maybe good introductory course for beginners of calculus. Not recommended for learns who seek for details of ideas.

автор: Kirill N

•16 авг. 2020 г.

Weeks 1-3 (4) were pretty nice; weeks 5 and 6 were terrible. The harder the topics, the less explanation was given, the pacing by the end was atrocious and course delves into statistical topics while it probably could've dedicated these weeks to other relevant topics.

автор: Yi Z

•3 авг. 2018 г.

Such a easy course, if you totally a novice in multi-variables calculus, you could take this course, Whereas, if you are familiar with calculus, it will be quite easy for you.

I hope more programming assignment about Machine Learning

автор: Rob E

•11 авг. 2020 г.

The instructor for this course actually tried to explain the concepts, unlike the other two courses in this specialization. However, no one is available to answer questions.

автор: Shivam K

•30 июня 2020 г.

I feel that the course was too fast paced. I had to constantly refer to many other website like khan academy and 3b1b. The course skipped many details and lacked intuition.

автор: pranshu s

•17 окт. 2020 г.

You will get some intuition of mathematics used in Machine Learning as well as there will be less fear in doing ML courses if you would complete this course.

автор: Alfred S

•13 янв. 2019 г.

Course would be prefect if there would not be technical issues with opening notebooks. It slows me down by 1 week. But content was really relevant to ML.

автор: kumar s

•9 авг. 2020 г.

Overall average course. Not that much good as expected because of David Dye. He was teaching very poor in this course as compared to course-1.

автор: TirupathiRao p

•21 мая 2020 г.

Last 2 weeks completely diverged. Failed to converge. I wish content was more elaborate.First course of this specialization was far better.

автор: MAYANK G

•4 июля 2018 г.

Role of discussion forum is very less. Please improve on that to have healthy participation. Otherwise, course content is really good.

автор: Kamoliddin N

•7 дек. 2019 г.

first 4 weeks were good. Starting from week 5 course explanation was bad. Was required to watch other videos.

автор: Lieu Z H

•18 нояб. 2019 г.

Lecture videos are quite sparse, and the quizzes test things that they don't teach you in the lecture

автор: Saurabh M

•29 сент. 2020 г.

A bit fast paced, could be much more beneficial with some added explanations.

автор: Lee j

•23 мая 2019 г.

Too fast to understand what instructors says.. but lecture contents are good

автор: Erwin M

•28 апр. 2021 г.

The basics is explained so light, that you wonder if it is of any use.

автор: Akeel A

•29 авг. 2020 г.

It was a lot of fun at points. Would recommend to anyone else.

автор: Gurrapu N

•7 апр. 2020 г.

Strong disconnect between teaching videos and assignments.

- Google Data Analyst
- Управление проектами от Google
- UX-дизайн от Google
- ИТ-поддержка Google
- Наука о данных IBM
- Аналитик данных от IBM
- Анализ данных с помощью Excel и R от IBM
- Аналитик по кибербезопасности от IBM
- Маркетинг в социальных сетях от Facebook
- Разработчик комплексных облачных приложений IBM
- Представитель по развитию продаж от Salesforce
- Сбытовые операции Salesforce
- Soporte de Tecnologías de la Información de Google
- Certificado profesional de Suporte em TI do Google
- ИТ-автоматизация с помощью Python от Google
- DeepLearning.AI Tensorflow
- Popular Cybersecurity Certifications
- Popular SQL Certifications
- Popular IT Certifications
- See all certificates

- бесплатные курсы
- Изучите иностранный язык
- Python
- Java
- веб-дизайн
- SQL
- Cursos Gratis
- Microsoft Excel
- Управление проектами
- Безопасность в киберпространстве
- Людские ресурсы
- Data Science Free Courses
- говорить на английском
- Content Writing
- Веб-разработка: полный спектр технологий
- Искусственный интеллект
- Программирование на языке C
- Навыки общения
- Блокчейн
- Просмотреть все курсы

- Навыки для команд по науке о данных
- Принятие решений на основе данных
- Навыки в области программной инженерии
- Навыки межличностного общения для проектных групп
- Управленческие навыки
- Навыки в области маркетинга
- Навыки для отделов продаж
- Навыки менеджера по продукту
- Навыки в области финансов
- Android Development Projects
- TensorFlow and Keras Projects
- Python для всех
- Глубокое обучение
- Навыки Excel для бизнеса
- Основы бизнеса
- Машинное обучение
- AWS Fundamentals
- Data Engineering Foundations
- Data Analyst Skills
- Skills for UX Designers

- MasterTrack® Certificates
- Профессиональные сертификаты
- University Certificates
- MBA & Business Degrees
- Степени в области науки о данных
- Степени в области компьютерных наук
- Дипломные программы по анализу данных
- Степени в области общественного здравоохранения
- Social Sciences Degrees
- Дипломные программы в области управления
- Degrees from Top European Universities
- Дипломы магистра
- Степени бакалавра
- Degrees with a Performance Pathway
- Бакалаврские курсы
- What is a Bachelor's Degree?
- How Long Does a Master's Degree Take?
- Is an Online MBA Worth It?
- 7 Ways to Pay for Graduate School
- Просмотреть все степени