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Avis et commentaires pour d'étudiants pour Apprentissage automatique par Université de Stanford

4.9
étoiles
140,526 évaluations
35,495 avis

À propos du cours

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....

Meilleurs avis

MN

Oct 31, 2017

Great overview, enough details to have a good understanding of why the techniques work well. Especially appreciated the practical advice regarding debugging, algorithm evaluation and ceiling analysis.

AD

Apr 22, 2017

Very good coverage of different supervised and unsupervised algorithms, and lots of practical insights around implementation. All the explanations provided helped to understand the concepts very well.

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101 - 125 sur 10,000 Avis pour Apprentissage automatique

par Tobias T

Jun 05, 2019

I've tried DataCamp and recently take my first course in Coursera. The difference is huge and important if anyone wish to learn more about ML or DS. This course does not focus much on 'just coding' the answer. It aims to teach you the logic, basic maths behind ML algorithms.

The coding exercise is challenging and fun aswell. It doesn't give you any 'fill in the blanks', so basically, after each exercise, you properly have some good understanding about the logic. Using Matlab/Octive is much better than I expect. Not that it is easy to use/understand, but it let you understand the Math better. e.g. when to transpose, how to use look at dimension before writing any codes. These exercises are at a level which you can easily transcend your understanding and knowledge to whatever Python or R you are using. !

par Arpit J S

May 01, 2020

Mr. Andrew Ng has mastery on Machine Learning. His method of teching is precise and lucid, often engaging us to think more on untouched aspects of ML. This was my first course and first step (a baby step) on any platform to understand and learn ML . Lucky to have enrolled for this amazing course and I sincerely thank him for being instructor on this subject and also tons of thanks to mentors who clear doubts in discussion forums. It helped a lot. Lastly , I think this course has clearly set my path towards advanced studies in ML. Although, statistics and some of the terms did bounce off my head few times, I hope to revisit and work on them more in future. Thankyou Andrew Ng Sir ! I am your fan now !!! :)

par Amirhossein B

Jun 03, 2020

I so appreciate it from COURSERA and DR ANDREW NG for this unbelievable course. It was definitely one of the best courses I've ever seen in my whole 20-year life. I'm from Iran and I have really restricted rules for having access to such courses. I'm so glad to have this opportunity to attend a class with a professor from Stanford University. I'm not good at English very well but I don't know why I feel that at the end of the class Prof NG was kind of sad from ending the course and I was nearly to cry seeing him like this. here I'm gonna promise this for the first time, I promise to spend my whole life to do what Prof NG did for me in this course, to help others. Thank you so very much.

par Vincent C

Sep 25, 2019

After finishing the course, I feel much more confident in pursuing more advanced machine learning. The course teaches everything intuitively and in detail but maybe it could use some improvement to achieve perfection. It would be better if the course could provide pointers to some of the topics beyond the scope of the course such as the derivation of the back propagation, svm, pca, etc. Because often times when you search for derivations they might not be very useful for your levels, if course could provide some good references as some lecture notes after the video would be great for the students to gain even more solid groundings of the things behind the hood

Super thanks and thumbs up

par Vamshi B

Jun 06, 2019

As a machine learning newbie, I can say this course is really helpful to get in depth intuition on how machine learning algorithms work. Techniques to evaluate and improve our algorithms are also explained very well. Programming exercises are really challenging. Review questions are also crafted well. Though this course uses Octave/Matlab instead of python for programming, I find it quite useful to understand and implement algorithms easily. Only negative of this course is, mathematics involved is not explained in detail. Overall, this course has helped me a lot to understand machine learning in a better and useful way.

par DEEPANJYOTI S

Mar 11, 2019

This is a very good course which gives a good solid foundation in the basics concepts of Machine Learning. Prof. Andrew explains reasonably complicated algorithms in a very intuitive way which goes reasonably deep, but at the same time doesn't overwhelm the student with a lot of underlying mathematics. The course structure also follows a very natural progression (linear regression --> logistic regression --> neural network --> SVM) and bringing in other basic concepts like feature normalization, regularization, measurements etc. along the way. Definitely one of the better designed courses I've seen so far.

par Anith S

Jun 06, 2019

This is the first ever course I have taken on Machine Learning and I have to say that it was the best course that I have ever taken till I have taken the DeepLearinig Specialization by Andrew Ng.

I would highly recommend this course for anyone who wants to break into Machine Learning. Because it starts with the very basics and builds on it.

It currently may be bit outdated considering that it is thought using Matlab and not Python but it is excellent in explaining the core concepts and the algorithms of Machine Learning.

It is still a good course for breaking into Machine Learning.

par Zheng Y

Feb 23, 2019

The course is very well structured for me, a student who has some understanding of machine learning but would like to get a systematic introduction of the subject.

The course strikes a balance between depth and breadth. The amount of math and equations are just right. Prof. Ng did a good job stimulating the students' curiosity to dive deeper. And for those who want to get practical and hands-on, this course contains enough tools for machine learning practitioners.

I would recommend this course to anyone who is interested in machine learning but do not know where to start.

par Walter E P

Dec 23, 2019

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.

par Vivek R

Mar 12, 2019

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.

par Harsh S

Jun 09, 2020

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.

par Jatin k

Jun 18, 2020

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.

par Subham

Mar 03, 2019

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.

par Martins R

Apr 24, 2019

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.

par Manish S

Feb 04, 2020

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.

par Emily C

Jan 02, 2020

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!

par Vaibhav J

Jun 05, 2019

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.

par Anup

May 21, 2020

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.

par Ken P

May 01, 2020

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 !

par Andrea R

Jul 03, 2020

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.

par Miklós L

Jan 15, 2019

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.

par Harshit A

Jan 13, 2019

This course is a really amazing and well taught course.Andrew sir is really a very good teacher and he made the complex topics quite easy to understand with his cool examples.Moreover, the optimization techniques and advises given for debugging or improving the machine learning program were really helpful. I hope I can take full advantage of this course and build up a career in machine learning.

par Shashank S

Sep 09, 2019

This course was splendidly awesome. I am in my final year from grade C engineering college in New Delhi, India. This course helped me a lot to understand about the basics and gave me deep understanding about the field. Thanks to Andrew NG Sir who made this great website for students like us and such an best class content. Highly Recommended to all!

Thank You!

par Pankaj R

Apr 19, 2020

Great Course to start with Machine Learning. All algorithms and technical expects are covered and explained in detail. Assignments are well framed and gives you a proper intuition on algorithms use and performance on real world data. Also appreciate the advise on debugging and optimizing algorithms on small test examples, before running on large data sets.

par Asmita P

Apr 08, 2019

Hi Andrew,

I liked this machine learning course so much. I enjoyed doing all the assignments. I am working in IT industry. I was thinking of working in a new age technology and then my brother told me about this course as I love maths and programming.

I am looking forward to get deep knowledge in machine learning.

Thank you,

Asmita Patil