Chevron Left
Back to Supervised Machine Learning: Regression and Classification

Learner Reviews & Feedback for Supervised Machine Learning: Regression and Classification by DeepLearning.AI

4.9
stars
23,866 ratings

About the Course

In the first course of the Machine Learning Specialization, you will: • Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. • Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications. This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field. This 3-course Specialization is an updated and expanded version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start....

Top reviews

FA

May 24, 2023

The course was extremely beginner friendly and easy to follow, loved the curriculum, learned a lot about various ML algorithms like linear, and logistic regression, and was a great overall experience.

AD

Nov 23, 2022

Amazingly delivered course! Very impressed. The concepts are communicated very clearly and concisely, making the course content very accessible to those without a maths or computer science background.

Filter by:

201 - 225 of 4,717 Reviews for Supervised Machine Learning: Regression and Classification

By Mrityunjay U

Sep 12, 2023

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.

By azer d k

Sep 23, 2024

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.

By Samuel B d S

Feb 23, 2024

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.

By Amir B

Nov 8, 2023

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 :)

By Suraj B

Jul 20, 2022

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.

By Alberto Y W

Mar 19, 2024

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.

By Anirudh N

Aug 9, 2024

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.

By Sudhakar V

Jul 11, 2022

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.

By Dave W

Mar 5, 2023

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.

By Jeffrey G

Apr 17, 2023

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!

By Samarth P

Jun 21, 2024

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.

By Ángel A A

Jun 9, 2024

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!

By Nikhil B

Feb 27, 2024

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.

By Priti S

Feb 8, 2023

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.

By Amirhossein S

Mar 14, 2023

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.

By Charlan D C

May 28, 2023

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.

By vinay k g

Jan 8, 2023

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.

By Luciana R

Jan 5, 2024

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.

By Darshit S

Apr 16, 2023

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.

By Md. A M

Jun 24, 2023

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.

By Ronald B M Z

Apr 4, 2023

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.

By Soumyadeep S

Feb 22, 2023

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.

By Mohamed A A A E

Mar 14, 2023

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!

By Sergio R M R

Mar 25, 2024

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!

By Namhoang

Sep 2, 2022

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.