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

4.9
stars
18,061 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.

JM

Sep 21, 2022

Specacular course to learn the basics of ML. I was able to do it thanks to finnancial aid and I'm very grateful because this was really a great oportunity to learn. Looking forward to the next courses

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201 - 225 of 3,771 Reviews for Supervised Machine Learning: Regression and Classification

By Girma S E

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Feb 10, 2024

A great introductory course into the world of AI! Much gratitude and thanks for the Financial AId. Before being approved for the aid, I tried other free online courses from d/t source, and I can 100% vouch this is the greatest. I really liked how Andrew presents the lessons, and even more how the course provides a solid understanding of the concepts in a detailed yet understandable way to a newbie like me.

By Shreyansh P

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Aug 20, 2022

A great course with well clarity of concepts. I have nearly no knowledge of most of the maths or statistics topics required for Machine Learning (such as Linear Algebra, Calculus, etc.) yet with time and determination along with some research of my own. I was able to fully understand and complete the course. The course breaks down certain aspects of Machine Learning very well making them easier to absorb.

By Naitik C

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Jul 26, 2023

I found this course very detailed with clear understanding of fundamental concepts of supervised machine learning. After a topic is explained there are labs for better visualisation of the topic. Optional short quizzes are present in the videos which help us introspect our understanding of the topic explained in the video. Practice labs are a great way to revise what we have learned in a collective way.

By Irene P

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Jul 3, 2022

With some Python experience, this was super hands on and easy to understand. I came into this course without a strong knowledge of how to decodify math algorithms, and with Andrew's super clear explanations and the super hands on optional labs, I found myself able to see how the alorithm was changing through visual graphs, and become able to apply the machine learning mathematical algorithms into code.

By Iyar

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Mar 4, 2023

Incredible course. Instead of completing it over 3 weeks, I took the time to simutaniously practice coding side projects whilst learning the concepts, and also took the time to catch up on my math skills. This in total took me 2 months, with a few breaks due to a lack of time. I absolutely recommend this to new learners, and also do recommend working on side projects like I did, alongside this course.

By Daniel A

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Jul 29, 2022

This is really a great course. Andrew Ng showed really great understanding of the and he was able pass it on by breaking the topics into atomic units. The labs were helpful and the quizzes were easy also. However, I would suggest that a complete project should be given and the whole code should be written by learner which can ensure they course was fully understood and further enhance their portfolio

By Muhammad U

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Aug 9, 2023

I am truly amazed by Andrew Ng's Supervised Machine Learning course! The content was incredibly insightful and well-structured, making complex concepts easy to understand. The practical examples and exercises were invaluable in enhancing my skills. This course has been a game-changer for my understanding of regression and classification techniques. Thank you, Andrew Ng, for your exceptional teaching

By youssef e

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Sep 1, 2023

In my experience, the course is of great value. However, I believe that incorporating additional programming assignments every week would enhance the learning experience. This approach would allow learners to put into practice the knowledge they have acquired from the video tutorials and solidify their comprehension of the concepts, thereby reducing the likelihood of forgetting them in the future.

By Raghvendra M

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Sep 16, 2023

Very well organised and delivered. Build the foundation of ML and then goes to details of Logistic Regression and how to overcome from the problems when your model doesn't perform well. The programming assignments are really good and you don't want to miss that as it is when we see the workings of Logistic Regression. Also, you get the opportunity to learn from the veteran of ML, Dr. Andrew Ng.

By Mohsen F

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Jul 17, 2022

This course was really good. The visualizations in the lab were really creative and insightful. By the way if felt like in the third week, the speed of teaching stuff began to increase, It was ok but i was shocked at first. I am a teacher myself, so i realize how much this team worked to prepare this content. I want to thank all members of this team one by one. I hope i can meet them soon. :)

By عبدو ع

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Jul 30, 2023

You may consider telling me that you can write the code in the quizzes in your way like when I was doing these quizzes I wanted to write it with np arrays broadcasting and vectorization [I did that anyway] but it was very confusing that there is a template of z_wb and f_wb inside nested for loops and I have to stick to this hierarchy. Thanks for the course, it was amazing and informative.

By Charles B

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Oct 30, 2022

The course focused on learning how to do the equations and programming for the algorithms. It gave a good understand of not just the algorithms but when and how to implement them. There was no time wasted on being concerned how to generate plots or gather test data for the assignments. That was done for us... which was a great help. All in all a very well planned and executed course.

By Fredrik Ö

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Aug 3, 2022

Had already completed the old course "Machine Learning". Took this course because of the switch from Octave to Python. So i thought it was a great idea to repeat what i had learned and at the same time sharpen my skills in Python. Really liked the enhancements, like the extra optional labs with Scikit. Also this was a preparation for me since i intend to take the 2 continuation courses.

By Sohail S

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Feb 17, 2023

This was an exciting ride, I enjoyed every bit of it. The explanation, the presentation, the examples, and the labs were up to the mark. I loved the optional labs, the way they were structured, and the way they explained every block of code is worth appreciating. Thank you, Coursera, and Stanford for providing such a fantastic course, looking forward to completing the specialization.

By Jeffrey C

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Aug 14, 2022

Terrific introductory course, but I wish it gave you the option for more hands on implementation of the supervised machine learning algorithms as you progressed. I could have easily passed this course with knowing the bare minimum, but I wanted to become proficient in the foundations, and unfortunately there wasn't much in the way of testing your knowledge without the training wheels.

By vijay s

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Aug 14, 2022

I felt after learning this, that my overall understanding has become very deep and now i feel very confident about implementing this in real life scenorio. It has given me clarity on "how to steps in Machine learning" . Very intutive and natural course for topic of vast calibre and application. Thanks to the team of coursera, deeplearning.ai and standford for sharing such information.

By Badavath T

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Jul 5, 2022

This course is fantastic, everything from the previous course but more. Adding Python instead of octave/Matlab is excellent, and the programming assignments are also beneficial. The teaching is exceptional as always. If you are looking for a course in machine learning, this is the best pick. I enrolled the day the course was released, looking forward to completing the specialization.

By Matthew T

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Nov 7, 2022

Very good - easy to understand instruction and enjoyable to listen to.

The lab's are excellent to take the theory and test it. I found using the labs was the best way to understand the maths and logic, and how the layers of iterations come together. Particularly in the last few lessons when you have operations happen on individual features, individuals examples and then the whole set.

By Th D

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Sep 10, 2023

Andrew Ng is a great teacher.The material is very well presented and Andrew makes sure the learners develop an intuition on the concepts of the course.As a side note i found the assignments too easy, but i can understand the philosophy of the course is not to discourage people but help them understand the concepts and give inspiration to enter the exciting world of machine learning.

By Argha B

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Jul 28, 2022

Andrew Ng is one of the pioneers in the field of AI. His original course, while very theortically enriched, was showing its age for the choice of its programming language. This new specialization was just the right thing for someone like me who needed to implement all the concepts in the de facto language of AI, all the while learning the said concepts from the leaders of the field.

By Alexandre C

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Oct 3, 2023

It is an introductory course, but it manages to go a little deeper than I expected. Obviously, do not expect any (or almost any) mathematical proof or deep explanation about veery topic, but you can expect to learn the mathematics behind logistic and linear regression, being able to implement then even without a package. Andrew's explanation about the logic of the models is great.

By π m

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Mar 29, 2023

this course was so impressive to me , from building up the intuition to practical labs as well as the optional labs , I have visited the concepts provided in that course before , but the way I understood those concepts in this course was new to me and added a lot to me , thanks for providing such valuable information in a very simple systematic way. Special thanks to Andrew :D

By Virender S

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Aug 5, 2023

This course is a very good start for beginners in the field of ML and AI. Concepts are explained very well by Andrew himself. Best part of the course is how Andrew tries to develop the intuition behind different algorithms. I had been reading some books to understand these concepts but it was hard. Now, I think, I have the foundation to understand different books on these topics.

By Ghulfam H

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Jan 23, 2024

Andrew Ng's "Supervised Machine Learning: Regression and Classification" is not just a course; it's an immersive learning experience. It's a well-structured roadmap, a friendly guide, and a spark for your journey into the exciting world of machine learning. Highly recommended for anyone who wants to understand, apply, and ultimately be inspired by this transformative technology.

By ZAIN Z

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Jul 12, 2023

Overall, the "Supervised Machine Learning: Regression and Classification" course on Coursera is highly recommended for anyone interested in mastering the concepts and techniques of supervised learning for regression and classification tasks. It will equip you with the necessary skills to apply these techniques to real-world problems and make informed decisions in various domains