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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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351 - 375 of 3,771 Reviews for Supervised Machine Learning: Regression and Classification

By Macton M

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Sep 2, 2023

I have struggled for so long in getting to understand how neural networks work. It turns out that neural nets are just simple logistic units arranged in some fancy ways. I decided to take this course and everything else unfolded after that. Thank you very much Andrew Ng, you an amazing teacher.

By Mike B

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May 26, 2023

Very well put together course and material. Good balance with respect to some explanation of the underlying mathematics while minimizing the need for immediate deep understanding of these concepts. Clear, concise and well articulated explanations with lab materials to reinforce learned concepts.

By rushabh c

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Apr 16, 2023

First of all, Thank you for making such great content. I was totally new to Machine learning but now I don't because this course was really well organized with explanations in simple language.

Thank you again for providing me with such a great platform to learn, it will really help in my career.

By Jaime J C C

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Dec 5, 2023

Very complete course explaining classical academical regression and classification models. Very practical approach but without losing at any time the rigorous mathematical foundation behind the algorithms you are using accompaigned of several graphics to gain intuition about what is being done.

By Chandra B

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Sep 4, 2023

This is the perfect course any one can do if they are starting their journey towards data science and machine learning. Andrew Ng is just an amazing teacher and the way he has explains each of the concepts is the best i've ever seen. I wish I had a teacher like him during my studies in college.

By Wayne K

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Aug 26, 2023

A really challenging course for someone my age (77) who has not had any advanced math classes in over 50 years and only an introductory class in Python. But I got the certificate for class 1of 3. This could have not been done without being able to progress at my own pace. Thank you Andrew.

By Bester M

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Jan 15, 2023

Very nice course. Anybody new to machine learning should be able to grasp the concepts with ease. It's a well delivered, well thought through and slow paced course designed for an effective learning experience. Big thanks to Andrew Ng and the team that put in the hours to develop this course.

By DEEP V S

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Dec 30, 2022

i really like the course. Its very informative and has good hands on labs. Just a suggestion, it would suit curious minds like me a bit better if links were provided where i could look at the details of the math behind or read a bit into what was taught beyond the course. Great work thankyou

By Rahul C

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Aug 19, 2022

Course content and all optional lab are very helpful for the student who are changing their field from Any industry into field of Data Science.

All content are helpful and easy to understand.

Thank you coursera team and Deep Learning team to provide such kind of learning platfrom for biggner.

By H L

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Mar 8, 2024

I loved the video lectures. They were simple but no compromise on quality was made. The labs tested only what was relevant to the course objectives. All the redundant stuff was handled by default. TLDR: The perfect course for someone with only basic knowledge of programming and mathematics

By Md. A I

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Dec 10, 2023

This is a great course for me. Two of the supervised ML problems Regression and Classification are discussed in sufficient depth, the building units of ML model and the mathematics behind them. I want to show my gratitude to Andrew Ng and other members associated with this amazing course.

By Prajwal Y P

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Feb 24, 2023

Very very very useful!! Neatly explained the 2 supervised machine learning techniques(Linear Regression and Logistic Regression) and with simplification techniques such as Scaling, Regularization, Vectorization and so on, beautifully explained. It is a resourceful course for ML beginners.

By Mohamed J

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Aug 6, 2022

This is the best course ever on Machine Learning (I hope it remains so in the future) . It was a honour to learn from the great Andrew Ng Sir. Thank you so much sir and to his team for creating such a great course. This course provides a great chance to #BreakIntoAI. I love this course !

By Tanya S

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Jul 2, 2023

The best course to get started with machine learning. Andrew Ng has done an amazing job of explaining these topics in such a simple way. The optional labs have also been very helpful. Also, the programming assignments and quizzes have been very helpful in understanding these concepts.

By Andrés R

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May 12, 2023

This course is killer. This is not the first time I'm doing this. The first time happened like 10 years ago when the course was given with similar approach and the labs were in Octave. It's super nice to see new material and wonderful to understand things with a different perspective.

By Vijaykrishna V

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Sep 29, 2023

Andrew Ng is the best teacher of the Machine Learning and AI concepts. Coming from a biology background, I really enjoyed Andrew's video lectures which explain some of the complex ML equations such as cost function, gradient descent in regression and classification in simpler terms.

By Marc S

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Dec 3, 2022

This course was incredible. I particularly loved the "intuition" training on the algorithms, so that one can actually see what is happening and how to best adjust things. I think Professor Ng might be the best online instructor I have ever come across. Thank you so much for this!

By Rudra S C

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Oct 10, 2022

Great course for beginners to Machine Learning. The vastly updated codebase to Python will be very useful for practiioners. The interactive model fits really gives a hands on exploration to beginner Data Scientists. Would be great if you can make the slides available for reference.

By Ovu S

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Jul 25, 2022

this course is by far the best i have ever taken , both physically and online, and one of the most important aspect of the course if you ask me, i will say it's the optional lab part of the course, because that's where you actually know how to bring the learning algorithm to life

By Wojciech S

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Nov 4, 2022

Very well explained material on linear and logistic regression (with some additional aspects like regularization, overfitting and underfitting). Knowledge is built step by step, which allows you to consolidate and organize the material. It is worth learning the optional exercises.

By Ganael D

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Feb 15, 2024

After completing this course, I have confidence in my ability to handle supervised machine learning projects. It was great! Andrew Ng is a fantastic teacher, everything was clear and easy to follow. I absolutely recommend this course to anyone who wants to learn machine learning!

By Khondaker H M A

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Nov 13, 2022

If I had to review it in a sentence, "This is the best course to get started with Machine Learning in the internet." I tried to learn machine learning earlier but failed. But this time Alhamdulillah I was finally able to understand the things. It will be suggestion to everyone...

By Shawn C

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Aug 5, 2023

An inspiring and exceptionally well taught course. In particular, despite the underlying sciences that culminated this topic, anyone can get started and learn many of the concepts, due to the quality of the instructions, to be inspired and start the journey in Machine Learning.

By Anna V

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Aug 7, 2022

Very clear, concise lectures and materials that were easy to follow. Enjoyed Professor Ng's enthusiasm and encouragment throughout the series. Most liked being able to watch videos and complete work on my own schedule, and also rewatch videos to understand better and take notes.

By Kshitij D

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Oct 27, 2023

I love the way this course is taught, and am very grateful to Stanford and Coursera for making it available. The labs are just amazing - rich with opportunities for building programming skills while also getting the concepts better encoded into our brains in an unforced manner.