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Great course. Andrew Ng teaches in a way that even a beginner with zero background knowledge about machine learning can understand pretty easily. The pacing is really good. The optional labs though mentioned as optional are extremely beneficial as the videos cover the theoretical part while the labs cover the basics of coding required. 100% recommended course if you are looking to learn machine learning as a beginner for academics or just to improve your skills.

The course covers the basics, which help understand the concepts behind regression and classification.

The labs are in python, which makes it easier to follow.

Programming the cost function and many other functions manually instead of just using the library helps understand the concept.

Finally, the instructor Andrew NG is calm and composed in explaining the complex concepts and making them easy to understand.

I thank the entire team for coming up with this course.

I'm returning to Machine Learning after an eight-year absence. Andrew Ng is able to convey not only the 'how' behind Linear and Logistical Regression, but also the 'why.' I chose to pay for this course instead of taking other courses that are available to me because of its didactic excellence. Kudos to Deeplearning.AI for their efforts to provide a first-class education, even at the beginning level. I look forward to proceeding onto the next course and beyond.

Wow! Great course! I was lost watching ML videos on YouTube, until this course came along. Now I have a good understanding of the fundamentals of machine learning. This course is a necessary requirement to be able to move on to advanced algorithms, neural networks, and TensorFlow. Andrew Ng explains things very clearly and gives what is needed to understand. The course materials and downloadable working python code examples helps get you started easily!

I am beginner in Machine Learning, this course and the instructor made it so much clear and easy to understand Machine Learning concept that now for me it`s not an alien concept. Don`t hesitate to opt for this course, though there is more emphasis on mathematical side I think its pretty to understand once you know the concept and its not too much complex either. I would 100% recommend any person to take this course if they are interested in Machine Learning.

El curso de aprendizaje supervisado fue excelente. Las explicaciones fueron claras y profundas, cubriendo tanto la teor铆a como la pr谩ctica de algoritmos clave como regresi贸n y clasificaci贸n. Aprend铆 mucho sobre los fundamentos matem谩ticos y la aplicaci贸n pr谩ctica de estos algoritmos en proyectos reales. Las tareas y ejemplos pr谩cticos me ayudaron a solidificar mis conocimientos y a aplicar lo aprendido de manera efectiva. 隆Definitivamente merece 5 estrellas!

I absolutely loved the teaching methodology and the quality of the content that was provided along with the practice lab. It was challenging and that's what makes it one of the best courses in the ed-tech market. I would highly recommend it to my friends and my fellow learners. I would like to express my sincere gratitude to Dr. Andrew Ng and Team for designing such a course that makes you the master of machine learning algorithm form basics to advanced.

Thanks Andrew for explaining the concept in details and also making it easier for us as beginners to understand. The course structure is very elaborate and the optional labs has helped me understand all the topics covered better in comparison to books on Machine Learning. The optional labs also has graphs where we could visualise the equations and logic implemented and even we can play and modify the equations and values to understand the topic better.

the first step is done!

special thanks to Andrew and his team and also 糖心vlog官网观看 to make this perfect course.

this course is really motivational and you won't get tired during the course, if you are hard work it guaranteed you will be passed it.

the content of the course is a combination of theoretical machine-learning mathematics that teaches in the simplest way thanks to Andrew and the coding section that help you to use these formulas in practical problem.

This supervised ML course provides a clear and concise introduction to key concepts like regression, classification, and model evaluation. It covers essential algorithms, including linear and logistic regression, with an in-depth look at regularization. The hands-on labs, practice quizzes, and real-world examples make it easy to apply the theory to practical problems. A great choice for anyone wanting to build a strong foundation in supervised learning.

The concepts taught in this course are relatively easy to grasp. However, I found the algorithms portion to be challenging, possibly due to my lack of foundational knowledge in linear algebra and calculus. Nevertheless, with dedication and perseverance, it is certainly possible to understand them. It took me about a month to complete the course, but I believe it will take me years to fully comprehend and internalize the complex concepts presented.

Such a good course! I did try out some ML courses on other platforms, but this one really made me stick till the end. Also, I love coursera's grading system and the way it asks us questions after every lecture. It really keeps the learning cycle healthy. I loved Instructor Andrew's explainations and vivid example on most of the concepts. If anything, I love the fact that this course generalizes a lot of the concepts into some daily life examples.

I acquired a good amount of knowledge by doing this course. I haven't done any machine learning course before, so the topics covered in this course helped me to understand the process behind the gradient descent algorithm and how it is applied to solve regression and classification problems. The programming assignments were good for understanding the code behind the functions that we generally use to solve regression and classification problems.

I really enjoyed the courses that Prof. Andrew taught. He has a special talent for explaining things in a way that's easy to understand. I learned a lot from him and it was a great learning experience. I think it's important to have teachers like Prof. Andrew who can make learning fun and interesting. It motivates students to learn more and enjoy the process of learning. Overall, I am grateful for discovering the courses taught by Prof. Andrew.

I took an LLM Engineering course on Udemy, which was very hands-on and awesome, but it didn't explain details of what we were using (by design). This course answered many of my questions after the 8-week Udemy course. Andrew explains the concepts clearly; even a beginner can understand them. I did find the code-writing labs challenging since I don't have a math background, so deciphering the math symbols was challenging, but I got through it.

I highly recommend this course to anyone interested in learning about supervised machine learning. The instructor, Sir Andrew Ng, does an excellent job of explaining the concepts in a clear and concise way. The course covers a wide range of topics, including linear regression, logistic regression, decision trees, and support vector machines. There are also several hands-on projects that allow you to apply the concepts you learn in the course.

If you're looking for a comprehensive introduction to machine learning, I highly recommend this course. Not only does it teach you how to hard code linear regression for regression and logistic regression for classification, but it also covers techniques to avoid overfitting by adding a regularization term. This course is essential for anyone interested in delving into neural networks, as it lays a solid foundation for further exploration.

Nothing has changed from the previous course of Machine Learning. Equivalently fluidic and exciting like the previous course. Adding python has helped a lot to progress through this course. Mathematically implementing MATLAB/OCTAVE for the functions was slightly difficult but python makes the work a lot easier. Thank you for this wonderful course. Looking forward to learning a lot more from the remaining 2 courses in the specialization.

I saw my self on an adventure from having no idea about supervised machine learning to now being able to create and trainsupervised ML algorithms myself. I am now even looking for datasets myself and practicing my learnt skills. A big shout out to Andrew for this course and for making it this easy to learn ML. I love the way you teach and how clear you are in teaching. What an adventure I have had taking this course! Thank you so much.

This course, the first in the Machine Learning Specialization, introduced me to the fundamentals of machine learning and offered insights into not only the theory but also the practical applications that will drive real-world solutions. As before, it was a privilege to learn about AI from Andrew Ng. Gaining hands-on experience with essential models has been invaluable, and I look forward to applying these skills to future projects!馃ぉ

I am a complete novice with a medical background and no programming experience whatsoever, but after completing this course I have a clear understanding of this topic as well as the code required to implement such tasks for similar data sets. Andrew is a fantastic teacher! I have moved through other similar youtube videos on this subject and in comparison I find this course excellent as it explains the concepts clearly and concisely!

The information was divided into interesting and concise videos, and everything shown was explained in order to be understood. It definitely explains the knowledge greatly and Andrew is a versed speaker and teacher! Depth was missing in regard to the fundamental mathematics and statistics, but it is not a focus of this course, but it would be good to still have access or additional information for people who are interested in such!

Though the course is divided into only 3 weeks but I felt like completed a 4-week course, since there are many videos and practices(mostly optional). As usual, the explanation and instruction of Andrew Ng. is really amazing, it should feel like lots of abstract concepts and terms but he did a great job breaking it into smaller parts and show the learning how things are done. Thanks Andrew Ng. and team for making such a great course.

This course is surprisingly excellent. I find the lectures by Prof. Ng to be easy to follow, extremely informative, and occasionally challenging. I do appreciate this newer version of the course that uses jupyter. I tried the older version with octave and I got bogged down dealing with the software installation issues, and never finished that version. I would highly recommend this course to anyone interested in machine learning.

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