Excellent overview of Regression and Classification. The labs were very useful in breaking down the logic behind the individual components of each ML method to help build a better intuition on how these models operate and why we might use them in select cases.

The Explanation of course is in-depth. while I was looking for Supervised Machine Learning: Regression and Classification with the help of sklearn. But, at the end of the course, I learn all the basic concepts in depth. Thanks for creating such good course.

This is an absolutely worth it course which introduces the basic algorithms of machine learning and is structured in such a way that it is easy to understand even for someone who is not very proficient in coding. Great Teaching by Andrew Ng. Loved the course

It is suitable for beginners and those who have studied it to review the course, which includes machine learning methods and ideas such as linear regression, logical regression and clustering. The course provides practical codes for everyone to learn. Great!

This course has really helped me understand the basic concepts of supervised machine learning in an easy manner. I am excited to continue learning and exploring the field of machine learning. Thank you for providing such a valuable and comprehensive course!

This is the very first machine learning course in my ML career. I enjoyed the way of teaching by Andrew Ng Sir. He is an expert in explaining complex topics in very simply understandable language. Highly Recommend this course for anyone who breaks into ML.

Exposure to lots of math I wasn't familiar with, but after multiple rewinds, they mostly made sense. Though, I'll be going back through my notes to review the material to prepare for the following courses. Definitely recommended for beginners like myself!

You will still need to practice what you have learnt but the content that is re-enforced with the labs are a great start. You can take any data set you want on Kaggle and jump right in with your first ML algorithm. The knowledge gained here is that good.

Thank you for the fantastic course! The beginner-friendly approach really helped me understand the concepts. The labs were great for demonstrating the practical applications of the mathematical ideas . I’m excited to apply this knowledge in my projects :)

He uses easy and mimic words explains complex mathematical theories which is well understandable. The optional lab is especially well designed which helped me a lot to understand the concept of linear Regression and have practical experience with python.

The course really was great, no doubt! I just wish there were more cognitive demanding exercises, say working on a project from start to finish with just little guidance, to really dial in the knowledge. But I really am excited to have taken this course.

I've taken a lot of courses on Coursera. This might be the best one. It took me a lot longer than the estimated 15 hours, mostly because I spent a lot of time studying the code that comes with the optional labs. For me, it was well worth the extra effort.

Great beginner class/introduction to ML. Clear explanations that go through step by step the equations/ calculations followed by what that looks like in code. Using simple, real-life examples also help to make the concepts easy to understand and digest.

I enjoyed this course a ton. The explanations the professor gave where easy to understand but got deep into the concepts he was explaining. He was able to communicate concepts really well and encouraged learning everything and even experimenting with it.

Andrew Ng being one of the best teacher taught machine learning concepts so easily. The best thing about the course was the labs. They provided good amount of material for practice the final assignments were very helpful in implementing what me learned .

Prof. Andrew is amazing! I have taken other courses before (also the older version of this course) but never got to finish any. This time a push myself to follow every task and finally did it. Looking forward to the challenges from the next two courses.

If you just start the journey of Machine Learning, I recommend you to start with this course. You will gradually know the science behind Artificial narrow intelligence starting from the simple well-known equation of a straight line. Thank you, Andrew,

The course material is excellent to learn the course's contents. Videos are very helpful for understanding. Assignments given in week#2 & 3 are really amazing for understanding coding in jupyter notebook.

We are very thankful for the teacher and others

It was the best course that I have ever passed. It was so practical and useful for me. My sincere gratitude goes to the instructor of this course professor Andrew NG and to Stanford university, Deep learning AI and Coursera for their financial support.

Thank you Andrew Ng sir and brilliant team of DeepLearning.AI , I have finished this course and start my interesting journey recently. I strongly recommend this new course in python which empowered by informative Lab and insightful visualization tools.

The teacher is really superb, makes the subject really simple to understand. Intuition chapters are specially helpful. Complexity adds up a little bit, but each layer is thoroughly explained.

Thank you Andrew Ng, and the team that made this possible!

Excellent first course on supervised Machine Learning. The explanations are very clear and the material, prepared by the instructor, is very didactical. I really enjoyed working on the notebooks and visualising regression and classification in action.

I am not new to python but new to machine learning and I feel like the course tought me a lot and also managed to simplify very complex subjects at the begining before stepping into details which it also does very well.

Andrew teaching is amazing ! .

Although most of this course was taught to me as a part of statistics course for my engineering degree, I appreciated how well the concepts were explained. This is a very good introduction for beginners to machine learning and regression in general.

Very good - I liked self-paced curriculum!'

Very nice lectures and well presented. Simplified enough, that I don't have to be a mathematician to follow the course.

Very good interaction with the labs to help me also see immediately the implementation!