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Отзывы учащихся о курсе Машинное обучение от партнера Стэнфордский университет

4.9
звезд
Оценки: 163,453
Рецензии: 41,933

О курсе

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas....

Лучшие рецензии

AB
30 авг. 2020 г.

A brilliant sequence of topics and fundamentals to get a stronghold on ML . The learnings I obtained from this course will always be my guiding factor in working through the projects in my life ahead.

YN
18 июля 2021 г.

Amazing really felt that I learnt something substantial. Very happy that I chose this course over others Andrew Ng Sir explained everything very clearly to a required level of depth.\n\nThank you Sir!

Фильтр по:

151–175 из 10,000 отзывов о курсе Машинное обучение

автор: John W

18 авг. 2020 г.

I would give this class 4.5 stars (rounds up to 5). Many different ML topics are covered, and they are presented at an appropriate pace for learning. The programming assignments are a great way to review the content and make sure you understand some of the details. Past experience with linear (matrix) algebra will be helpful but not required. Be sure to consult the resources that are available, especially the errata (it was a little disappointing how many small errors are present) and the lecture notes. But overall, I highly recommend this course.

автор: Walter E P

23 дек. 2019 г.

Great Course!. I took this course after having been formally trained in topics such as Numerical Optimization, Neural Networks, Genetic Algorithms, Linear Regression and other topics and I found these classes to be both very informative and refreshing. Learned something that sometimes some courses out there forget to mention which is how to draw meaningful statistics to analyze your algorithms performance and also things like what do work on next. I definitely advice people to take this course even if you are a pretty advanced learner on these topics.

автор: Paweł M

24 мар. 2021 г.

Fantastic course! I highly recommend it to anyone who wants to look a little more "under the hood" of ML. There are many courses that simply teach you how to use certain tools, such as Pandas or Tensor Flow, but often without explaining what the algorithm does or what kind of math operations are involved. This course shows it, but fear not - it's not as mathematically advanced as it could be - just enough to understand the topic. Professor Ng is a great teacher, I wish my professors at the time I studied were like him. Thank You Professor Ng!

автор: Vivek R

12 мар. 2019 г.

This course is very well designed, covers a lot of topics with a lot of rigourous detail, but Andrew Ng introduces them giving some intuition about them, before diving into the deeper Maths. Assignments are very challenging, but with some boilerplate code already done, they are immensely satisfying, as you end up achieving with some implementations of pretty cool problems. I have done linear algebra and regression and PCA before, so was able to complete it rather quickly, but this should be very approachable and useful for everyone.

автор: Kohei K

2 окт. 2020 г.

I am based in Tokyo, Japan and working for Marketing in Hewlett-Packard Enterprise. Marketing is now digital and data driven. In order to improve marketing data science skill, I took this course. This course and Professor Andrew Ng is amazing and could learn Machine Learning comprehensively. Recommendation system and clustering is very relevant to marketing job and would like contribute to the world based on the knowledge what I learned in this course. Many thanks for your guidance and great teaching, Professor Andrew san !

автор: Allyson D d L

18 авг. 2021 г.

This course was so amazing for me, because I always wanted to understand more about AI and neural networks but I did not find these informations easily. But this course was a nice introduction about AI and machine learning and I am so excited to learn more and more about AI after this course. I also started my first personal project with the knowledge acquired with the course.

I have just a bad commentary because the last 2 weeks did not have programming exercises, and it was needed to train the skills mentioned in the videos.

автор: Tomasz C

14 апр. 2021 г.

Bardzo polecam ten kurs, jak i wykładowcę. Andrew Ng świetnie przekazuje wiedzę, bardzo czytelnie i spójnie przedstawia cały materiał (w naukowy sposób). Na forum kursu można znaleźć wiele przydatnych informacji, a mentorzy pomagają i bardzo szybko odpisują na wiadomości. Świetne zadania z programowania (głownie w Octave) które opierają się na realnych przykładach i wymagają od nas zrozumienia algorytmów (wzorów). 100/100. Serdecznie dziękuje bo wiem że wymagało to dużo pracy, aby stworzyć tak dobry kurs.

автор: Harsh S

9 июня 2020 г.

This course is an amazing and extensive resource for machine learning, that isn't afraid to dive into the math behind ML. I thoroughly enjoyed all the intuitive explanations and examples given by the instructor. By focusing on the core concepts of ML, rather than on a specific programming language or library, this course ensures that it stays relevant even years after it was released. Overall, this course may be a little challenging for some people, but it is certainly worth all the time invested in it.

автор: Jatin k

18 июня 2020 г.

A very good course for beginners who want to study machine learning. Mr Andrew Ng is a very good teacher and very experienced in machine learning. The course structure is what it should be for an ML course. Programming exercises are really brainstorming and must be solved. Online threads can be used to seek help from other students and mentors, and are really effective. Reading slides are important for making notes.

This course is a very good and effective platform to learn machine learning skills.

автор: Subham

3 мар. 2019 г.

The real way to learn Machine Learning is this, no black box;understanding using pure mathematics makes it more interesting, and as I was solving the programming exercises I got to know, how simply vectors and calculus can be used to represent complex mathematical formulas. All the hours completing this course was worth. Once I started using machine learning libraries, all concepts were no longer black box for me, suddenly everything started making sense. Highly Recommended course for beginners.

автор: Elektrons

24 апр. 2019 г.

This was the hardest thing I've done in ages. I gave up at some point until a breakthrough in programming - I learning to use operations with matrices. I did all programming assignments in python. Couldn't finish the Neural Network - I was stuck for a month because I couldn't wrap my head around mathematical operation in backpropagation. Overall this was a journey. Every morning and evening learning on the way in the bus to and from work. Also lonely weekends. Finished. Can't thank you enough.

автор: Manish S

4 февр. 2020 г.

It is an amazing course for beginners who wish to know about Machine Learning. Taking the course and getting high-level knowledge of how different ML Algorithm works can be very useful and (in some cases, it is must) before using any libraries to create solutions. And for such cases, this course is certainly one of the best.

I sincerely thanks to Andrew Ng for taking out his time to make this course for a student like us. I highly recommend anyone to take this course with no hesitation.

автор: Emily C

2 янв. 2020 г.

A great introduction to Machine Learning. Found the pace of the lectures just right with a good balance of theory, worked examples and practical tips. I did Maths with Statistics at university and so found some of the concepts familiar but great to refresh! The coding assignments were well-explained and was able to walk through them step-by-step with the instructions. Really enjoyed the course and excited to start testing it out on some problems of my own!

автор: Vaibhav J

5 июня 2019 г.

The explanation of each and every topic is so simple and easy. The course is taught by prof. Andrew Ang and covers the major concepts of machine learning. He also provides a good intuition about the topic so to understand them better. Overall this course is awesome and I would highly recommend to someone who is a beginner in Machine Learning. I am very grateful to Professor, Mentors and the Coursera for this amazing journey of 11 weeks in machine learning.

автор: Issam B

7 дек. 2020 г.

I'm 50 years old and never thought that a career change can happen at this stage. This course gives you the basics and knowledge of how your trained data is fitted into a model; then used to predict/estimate the output of your next set of data. More importantly, it gave me the confidence to go deeper into the field of machine learning. I'm enrolling to get certified in "Deep Learning Specialization" on Coursera. Maybe we'll meet in your next AI adventure.

автор: Anup P

21 мая 2020 г.

This course i actually the first decent course I have taken in Machine Learning. It's really good if you have absolute no idea about what machine learning is. Don't fear the math, because Andrew (the instructor) really explains everything really good. Although a bit of programming experience is necessary, you can cover it while watching the lectures. I wanted to say the Instructor and the Mentors THANK YOU for sharing these extrordinary material with us.

автор: Burak C Y

14 февр. 2021 г.

I guess it's been a good start for me. At the beginning it was a bit challenging but after passing couple of weeks it got easier to understand. I think I have learned a lot and I am planning to do more, thanks to the Prof. Andrew Ng, who is the one of the best and most kind teachers I have ever seen. Everything he explains is pretty clear. And the motivational speeches that he made several times were really encouraging. I strongly recommend this course!

автор: Ken P

1 мая 2020 г.

Amazing Course by an amazing professor ! I am a Mechanical Engineer, and don't have any IT / Data experience. But even then how Professor Ng laid down ML foundations and took the course forward was very smooth. I am glad I took this course and I hope that the Professor keeps coming out with more advanced videos on ML. Thank you Andrew Ng for the months of work and dedication you put in for coming out with such a brilliant course for us students !

автор: Andrea R

3 июля 2020 г.

Best online course I've ever taken so far, and it's free! Please keep it always free! ML is not my field but thanks to this wonderful course I now have a very good high-level grasp of the argument as well as some technical knowledge to start tackling real-word problems. Andrew Ng is an exceptional teacher. Assignments are a great way to commit theoretical concepts to memory. You will also learn the basics of Octave/Matlab which is useful per se.

автор: Miklós L

15 янв. 2019 г.

Amazing class, great lecturer. A really good introduction and overview of machine learning concepts. It often skips the detailed mathematical background, to make it accessible for a wider audience, but I still found that enough information was given that allowed me to work out these details on my own. A lot of effort was put into creating the programming assignments, they provide a great hands-on experience with machine learning algorithms.

автор: Sara L

27 февр. 2021 г.

By far the best course you find online to learn the fundamental and math behind machine learning. Despite my hectic life and work schedule, I am grateful and so glad that I took the time to complete this course including all programming assignments and quizzes. I highly recommend this course for anybody who wants to build a strong foundation on AI science and has a sound understanding of linear algebra and some programming experience.

автор: Antonio R

23 июля 2020 г.

Although this is an introductory Machine Learning course, it covers all the important aspects and all the common algorithms, the programming skill is not so necessary with Matlab, a production-ready software, or its free software clone Octave, even if it is needed GPU acceleration. This course was much easier than I expected, even considering the lack of unnecessary mathematical theory, it was teacher Andrew Ng who made it possible.

автор: Sparsh K

23 авг. 2020 г.

Hello this is Sparsh kaushik and i just completed my ML course offered by Stanford.

To be honest this course offered exactly what i was looking, a proper Introduction into the world of Machine Learning.I really appreciate the efforts of prof Ng for making this course and all the mentors who guided me throughout the course.

Overall this course is a must if you are new to ML and want to dive into this beautiful word of data.

автор: Varadharaj P

31 дек. 2020 г.

This is the most interesting course that I had ever taken. I want to thank my tutor Andrew Ng for teaching those wonderful things. This course even changed my career path and also made me superior to my teammates by knowing these cool stuff. I have also designed some applications using the concepts I had learned in this course. Lastly I am grateful to my tutor @Andrew_Ng for make profession life more fruitful.

автор: Alexander H

22 апр. 2021 г.

This course teaches the fundamentals of Machine Learning very well. Although the use of Octave can be questioned, the exercies generally served as a good addition to the lecture videos. Aside from minor complaints like not editing mistakes from the videos in some occasions, i am very satisfied with this course! Perhaps Prof. Ng could reshoot the lecture videos to improve the video quality in the future.