I thoroughly enjoyed the course 'Supervised Machine Learning: Regression and Classification' by Andrew Ng. The way he explained the material made even the more challenging topics easy to understand. I learned a great deal about machine learning, with detailed explanations that made complex concepts accessible. Thank you for such a valuable learning experience.

Coursera’s Supervised Machine Learning course exceeded my expectations in every way. It provides a thorough grounding in supervised machine learning, supported by excellent teaching and practical, hands-on experience. Whether you’re a beginner or looking to deepen your understanding of machine learning, this course is an outstanding choice. Highly recommended!

The course is very well done and I'm pretty sure you'll be listening to Andrew with excitement and great focus. Unfortunately, if you're already skilled in algebra, calculus or programming, I don't recommend this course for you, as it's for complete beginners, and a lot of time is spent on explaining fundamental things in quite mathematically informal manner.

Supervised machine learning, encompassing regression and classification, is a powerful approach to make predictions and decisions based on data. It's crucial to understand the concepts, choose appropriate algorithms, perform careful feature engineering, and evaluate models effectively to achieve accurate and reliable results . Thanks to Coursera Authority

It was a great learning experience. Andrew has been an excellent teacher. I never felt at any point that the course was getting heavy on me. He explained each and every aspect with extreme detail.

But I do suggest to add Lasso Regression and Ridge Regression. Although a part of Ridge Regression was covered in this course, it was not emphasized upon that much.

Developed lots of mathematical intuitions, had fun labs which I must say were absolutely beautiful, notebooks provided by the instructors were phenomenal, I would recommend the course for the labs!! Just watching the videos and doing quizzes is *not* enough and the instructors know that.

I am grateful to Andrew and team for the wonderful work they have done.

Excellent course, I learned a lot. In particular, looking at the algorithms, logic and mathematics behind machine learning gave me an in-depth understanding of how it works and how programs are built. With so many Python libraries, it can be difficult to navigate the program, with this course I was able to understand the libraries used and their strength.

This course help me understanding the basics of Linear regression and Logistic regression. Andrew Ng is explaining every point deeply and It's easy to go with the course.

With the lab material provided, it is find to polish the skills and understand how things actually work. I liked the course and it is very good for someone who is new in machine learning.

Since this is my very 1st course ever in field of Machine Learning (career switch from civil engineering domain), I am very thankful to Dr Ng for making the tough terminolgies so easy to understand. The practical assignments (python programming) is what makes this course industry oriented. Thank you so much for this masterpiece Dr Ng !

Regards

Kasib Ahmed

ML concepts very well explained. For practicing and actual world challenge additional resources on Numpy, Tensor Flow, Keras are required. Professor makes this a cake walk to understand core of machine learning concept for new to the field. I am weak in programming still I could see (experience ) the vast expanse of this alien world of machine learning.

Sir's explanations is excellent ,I learned and enjoyed all the videos and practical lab so that's why thank you respected sir and thank you Stanford University to give me this course in free. Lastly I requested to the university please give me the remaining 2 course for free because I want to learn but I have no enough money to buy the remaining course.

very good course and one of the best part of this Course it do not use library directly rather than it use traditional mathematics and show how mathematics is the language of the ml or universe and make your confidence very much high and you will not only love this course but also feel every part of the lecture ,every algorithm how they actually work.

Excellent course. Great introduction to supervised learning. It helped me cement much of what I already knew on the subject and also gave me a deeper understanding of the course subject. Thank you very much Andrew and the DeepLearning AI team as well as Stanford University and Coursera for this course. I recommend it to any beginner to machine learning!

Excellent course and taught at a good pace which was very helpful for a working professional like me, as I had to squeeze in classes whenever I could. Loved the instructor, Andrew Ng, as well. The explanations were simple, precise and complete and that made a difficult topic seem easier. I'm inspired me to take on a few more courses in Machine Learning!

This is the best course on the internet for supervised machine learning and its basic algorithm. I learned a lot of new concepts from this course and I hope to learn new things after this. Andrew Ng is an awesome instructor . I loved the way the whole course was conducted. All of the topics were simplified and optional labs were very helpful as well.

This course is like a milestone in my career. The very well-structured material was brilliant among other educational courses I ever had. As a person who had no idea about ML, it was a perfect beginning. Also, the encouraging tone of Dr. Andrew Ng alongside his clear educational path in this course is motivating to keep it alive all the way to the end.

Thank you so much Andrew and team for these excellently curated machine learning courses. I'm going 2 out of 3 now and I am not losing any momentum because of how you explicitly you explain everything from the main topic down to every details. Again, thank you and I'm hoping I can apply the learnings from this specialization on my work and research.

excellent course, the exercises could have been more extensive but overall it's very good. I recommend carefully going through all labs . It will help you not only understand but implement code yourself. Also if you are not familiar with multivariate calculus and linear algebra, you should do that first to get better understanding of what's going on.

It is a very good course for the beginner to start learning ML. It includes learning of regression algorithms like linear regression, logistic regression, and regularization techniques. It helped me a lot to understand these topics. I would like to thank Stanford and the team for making available this type of courses with the option of financial aid.

An amazing and comprehensive learning experience and a great way to start with machine learning from ground zero. Being someone with a limited experience in the Python language makes it a bit challenging but still accessible. I really appreciated Andrew's calm teaching style and his great attention to detail. Thank you. Looking forward for course #2.

for someone who knew about ML as much as you would know about the universe from the pop science books, I think this course really dove into the subject with real math and implementations. I can now write python code that can get the program to learn solutions on its own! it almost feels like magic. :)

Thank you Andrew for being such a great instructor

This is an excellent course in ML. Andrew Ng is a brilliant instructor who motives the theory with fun real world examples. It is however a bit of a leap of faith to classify this as a beginner level course. The prerequisites to be able to follow along confidently are a crash course in Python together with undergraduate level algebra and calculus.

Its a very good course. I knew nothing of ML but after doing this course I am pretty confident that I can implement any supervised machine learning algorithm from scratch. Its beginner friendly. If you are afraid of mathematics and machine learning, you should take this course, because all your fear would be gone by the time you finish this course.

This course is designed to help you grasp the basics of all machine learning models and the math that goes with them. By the end, you'll have the knowledge to work with common regression and classification models. In short, it's a highly recommended course for anyone looking to understand machine learning fundamentals and apply them practically.

Explicaciones claras y buen material de laboratorios para acercarse al contenido mediante experimientos y visualizaciones. El único punto del curso que podría mejorar son las tareas de programación: considero que tener una mayor cantidad de ejercicios a realizar, quizás más breves pero más frecuentes, haría más fácil asimilar el contenido dado.