The course is very well structured and presented and the concepts are so well explained that it is easy to grasp them and I had a lot of fun time getting a more in depth knowledge about ML. I am a Product Manager and was looking for a course which gives me a good overview about the mechanics behind ML but also for which problems it is suited and since I could not find a course for just PMs I decided to take this one and didn't regret my decision for a second. Every PM working on a ML projects should take this course.

Very well put together materials and instruction. I had taken Ng's earlier course on this topic ( using MATLAB/Octave ) about five years ago and I found much of the details to be rather opaque due to the highly vectorized ( albeit elegant ) code. Breaking all the components open explicitly using loops in Python gave me a more effective framework for learning in this version of the course. Ng and his crew have nailed it here - a 'goldilocks' treatment of the material - not too difficult and not too easy either.

First of all thank you very much Coursera and team and very big thanks to prof. Andrew for give the opportunity. I am truly Satisfy with this course and throughout this course i learn so many things for the basic which new for me at least.. i will use my this new knowledge for better future for me along with society. Once again thank you very much team Coursera and special thanks to Prof. Andrew Ng. I will also recommend my friend my college who want to learn more and more deeply.

Thanks &Regards.

-Harshil Vasani

While I expected this to be simple Python refresher on the originally taken old course with MatLab/Ocatve, carefully reading into the code before executing it helped to conceptualie what I amd doing more. Also I really appreciate the interative demos, and especially those of gradient descent - they really add so much more to building your intuition -- make sure to click in the horizontal direction more anf more to the right and think why the results are changing in the way they do...

Thanks for this experience!

Thank you for the opportunity to take this course through financial aid! I enjoyed the way the course is structured including the optional practice labs and the programming examinations! Being a graduate student with lots of responsibilities, the flexibility of the course allowed me complete the course at my pace without which I would not have been able to complete the course. I would like to take the remaining 2 more courses in the series to give me a proper grounding in the Machine/Deep learning. Thank you!

I, a 16 year old high-school student, am oddly interested by Machine Learning, never having learnt it in school prior to this. Even though, I lack quite a few skills and had to try hard to understand certain stuff being discussed , the optional labs throughout this course made it easier for me to understand what I was supposed to do and made everything easy. I particularly loved learning and the questions at the end of the videos made me stay motivated to be attentive. Thanks for the wonderful teachings.

It's a great start towards Machine Learning Career, with this course You'll be able to apply supervised machine learning to solve real-world problems with the industry standard and best practices. You will know the application of supervised learning and how to implement supervised learning techniques to get things done without too much efforts and this course provide you hands-on experience and visual learning to describe the concepts and logics that are required in problem-solving and domain expertise

This course was broken down to smaller understandable pieces beautifully. The in-video questions were great and the all the labs were very well designed to soak in all the theory components.

I come from a place where I am scared of Math. The way it is taught helped me embrace ALL the Math seamlessly!

Congratulations to the team!

From a place where I was wondering am I good enough for this learning, to completing the course, congratulations to me as well :)

Can't wait to deep dive into the next course :)

Really good. All the provided codes are amazing, and I found them challenging. The course offers a perfect insight into what machine learning is. Everything progresses as outlined in the program. The videos are not too long, which prevents the audience from becoming tired. The labs are great. The codes for interactive plotting are my favorites, and I spent a lot of time learning and viewing them. I'm happy to have taken this course and recommend it to everyone seeking knowledge in this subject.

A very in depth course that lets you dive in into the world of Machine Learning. I think people that already have some python knowledge will enjoy this course more. Optional labs also aren't really optional, unless you simply want to hear lectures on linear algebra and calculus. In parallel with this course I recommend studying and practicing on modules like pandas, numpy, and matplotlib - that let me enjoy way more the course itself, than what I assume it would have been without some knowledge.

This is an excellent course for beginners in machine learning. Andrew Ng, a world-renowned expert in the field, teaches it. Andrew does a great job of explaining the concepts in a clear and concise way. He also provides plenty of examples and exercises to help you solidify your understanding of the material.

I highly recommend this course to anyone who is interested in learning about machine learning. It is an excellent introduction to the field and provides a solid foundation for further study.

I really adore listening to Mr. Andrew Ng, especially when he tells something along this line, "You don't need to worry about that." This course is very beneficial for me, because I am training to become a Machine Learning Practitioner. What I learned from this course will really be what my job will be. Thank you Mr. Andrew and to the whole team who developed this course. You have developed in me the intuition I need to be an equipped and responsible Machine Learning Practitioner in the future.

The course was pretty accurate, since being a new learner I didn't face any difficulties in understanding it as the course contents was very well described and precise. The optional labs was also very helpful, and the user friendly codes where you can play with it was quite exceptional. I looked forward to continue this journey with coursera in the field of Machine learning. My sincere thanks to our instructor Andrew NG as well to his whole team for such remarkable teaching and coding skills.

I’m absolutely buzzing! Andrew has a way of explaining things that makes even the toughest concepts feel easy to grasp. The course is well-structured, with a great mix of theory and hands-on projects that helped me apply what I learned. I loved every minute of it! I feel more confident in my machine-learning skills and can’t wait to dive deeper into the field. If you’re thinking about taking this course, do it! You won’t regret it. Huge thanks to Andrew for such an amazing experience!

One of the best course on Machine Learning on the Internet. The teaching methodology of the instructor is amazing. He is humble and explains everything from maths to the implementation of models from scratch and also with the help of libraries. The lectures are so well organized and well planned. This course actually set up the fundamentals of machine learning very strong with all of the insights + maths + coding. It actually helped me a lot about what actually ML can do in reality.

Excellent course! Clear insight given by Andrew on complex concepts using simple examples. Alternative way of teaching this course would be getting into linear algebra and calculus, but then then learners would have missed practical aspects of this course. I liked the fact that the focus is on practical applications. Optional labs were very useful. They gave crisp demonstrations of concepts covered in the videos. As a beginner with python, I learnt a great deal of pythons as well.

The “Supervised Machine Learning: Regression and Classification” course is one of the best machine learning courses available, taught by the renowned Professor Andrew Ng. The course is notable for its comprehensive content, hands-on projects, and excellent student support, making it an incredibly informative and valuable learning experience for anyone interested in machine learning. The teaching methods make complex concepts simple and accessible. I highly recommend this course.

O curso é excelente, o instrutor tem uma dinâmica ótima de ensino, os questionários são de acordo com as aulas, os laboratórios mostram como transpor da teoria para a prática, sem sombra de dúvidas é o melhor curso online que eu já fiz, estou muito feliz com o aprendizado que venho tendo, e também em descobrir esse universo vasto e interessante que é o aprendizado de máquina. Já estou animado para colocar os conhecimentos em prática em tarefas do dia a dia e também na faculdade.

"Thank you very much for providing such clear explanations in the Supervised Machine Learning Regression and Classification course on Coursera. The clarity of your instruction greatly contributed to my understanding of the material. I appreciate the effort and expertise that went into creating this course. It has been a valuable learning experience, and I feel more confident in my understanding of regression and classification. Once again, thank you for your excellent teaching!

Súper bueno, estaba esperando este curso en la versión de Python y me encantó. Se enfoca en entender gráficamente cómo funcionan estos algorítmos de tal manera que uno pueda jugar con las variables y los datos para ver visualmente como cambia el proceso de optimización. Una vez se entiende gráficamente se procede a ver las matemáticas detrás de esos algorítmos, las cuales entran más facilmente luego de haber entendido el proceso visualmente y didacticamente. Súper recomendado.

Very good structured and step by step explainations. The practical parts were not always easy but a very good proof of the individual undersanding.

After completion I will certainly have a look into the examples just for refreshing after finishing and gaining the full picture.

Very good, even my son studying AI did already know who the lecturer is: One of the best world wide.

What shall I say more? Learning from the best in the world is always a pleasure and a benefit forever

El curso es muy claro y bien dictado. Es me jor que el curso de achine Learning que estoy tomando también con NG. Recomendaría unos ejemplos mas trabajados y un curso previo de Python, pues esta es la parte que me costó mas trabajo. Aunque los ejemplos son en Jupieter, hay mucho software oculto que uno no puede entender y analizar. Lástima que por los costos no pueda continuar con los demás cursos, por eso quedo a la espera de la ayuda financiera.

Gracias

Carlos J. Gorricho

This course has helped me to understand the fundamental concepts of machine learning and has provided deep insights to various algorithms that are used in machine learning. This is a beginner friendly course so anyone who just wants to learn machine learning without having any prior experience in this field can take up this course. Taking this course was a very good decision and this course has provided me with a basic knowledge and understanding related to machine learning.

An excellent teacher, with high-quality (and addictive) lectures which really motivated me to continue into the domaine of Machine learning and Deep learning ! I highly recommend this course for everyone, especially for beginners who want to know more about the field ; the flow is nice, it's easy to follow at your own rythm and doesn't require much skills prealably, so very accessible. Thanks to Stanford University and Coursera for this first experience that I enjoyed a lot

I completed the Machine Learning course a few years ago and wanted to refresh my knowledge with this new speciality course. I think that this course was far superior. The use of Python in conjunction with the Jupyter notebooks isa big improvement over the Octave/Matlab usage in the first course. And my congratulations to the builders of the optional labs. They are extremely detailed and appear to have taken a lot of work in design and implementation.

Thank you.

Tom Mone