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

The course content is well-structured, Andrew Ng's teaching style is exceptional; he has a unique ability to explain complex concepts in a simple and intuitive manner. One of the strengths of this course is the hands-on approach. The programming assignments using [programming language] and [machine learning library] were challenging but immensely rewarding Thank you, Professor Andrew Ng, for sharing your expertise and making this course accessible to learners worldwide.

All the 3 courses have a good pace to follow. Concepts are explained very clearly and succinctly. Although I know this courses are not for coding experiences, from my point, expanding application examples is needed to understand the concepts better from different sectors and it would be better if this expansion would be as an article to be implemented to code by students. Overall, thanks to everyone in that project, it was a smooth and beneficial learning experience.

É um curso excelente o Andrew Ng tem uma didática excelente fazendo com que o curso seja prazeroso de se fazer abordando tópicos de machine learn focados em regressão linear, classificação, regressão logistica. No curso ele procura aprofundar e falar sobre o funcionamento detalhadamente de cada um dos processos de machine learn não apenas mostrar um sistema "caixa preta"- scikit learn ou simplesmente falar que regressão é uma reta que melhor se aplica aqueles dados.

i think this machine learning course was amazing, i learned quite alot , i now understand so many concepts and techniques thanks to the great instructors , videos and also the labs i was provided with. the quizzes and also the question in the videos made sure i payed the required attention needed to learn the concepts required. Overall i want to say a big thanks to mr andrew ng and all the people who have made this machine learning specialization course possible :)

This is the best course for revising the fundamentals of Supervised ML. I enjoyed the thorough explanation by the course instructor Andre Ng. Many topics covered in this course such as Regularization, Overfitting, and Gradient Descent are building blocks for Deep learning(NN). The practical approach for the implementation along with the conventions stated by Andrew makes this course the best among all. Overall, I enjoyed a lot learning the first part of this course.

I just finished Coursera's 'Supervised Machine Learning: Regression and Classification' course, and it was fantastic! Dr. Andrew Ng's clear explanations and engaging lectures, along with interactive quizzes and assignments, made learning a breeze. The high-quality videos and slides enhanced the experience, and I now feel confident in my understanding of machine learning concepts. I highly recommend this course to anyone interested in diving into machine learning.

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 teoría como la práctica de algoritmos clave como regresión y clasificación. Aprendí mucho sobre los fundamentos matemáticos y la aplicación práctica de estos algoritmos en proyectos reales. Las tareas y ejemplos prácticos me ayudaron a solidificar mis conocimientos y a aplicar lo aprendido de manera efectiva. ¡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 Coursera 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.

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 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.