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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

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

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.

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801 - 825 of 4,720 Reviews for Supervised Machine Learning: Regression and Classification

By Rohit M

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Sep 30, 2024

This course is excellent. The explanations of the topics are clear and presented in an easy-to-understand manner. It’s incredibly useful for building a strong foundation in machine learning.

By Manvendra S

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Jul 9, 2024

The course is best to start with the fundamentals of Machine learning. The course mainly focuses on the theory part and it is the most missing in any other ML course available in the market.

By Anwar K

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Nov 28, 2023

Great introduction to Machine Learning. Realising that my math is rusty and need to perhaps take the deeplearning.ai math courses. Professor Ng makes materials relatively easy to understand.

By Kevin G

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Aug 9, 2023

The best course I have taken. it translates a complex subject, into something very simple, and what I like the most about this course is how this thing unfolds step by step, until the result

By saurabh d

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Apr 24, 2023

I really liked this course. I had been doing regression for good part of my career, but I had missed the terms / labels and was not able to communicate effectively. This has helped me a lot.

By Maha A B

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Feb 11, 2023

i really liked the course, but because i am a beginner i will understand more about machine learning especially cost function logistics. after that, i am going to complete the next 2 courses

By Michael M

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Feb 6, 2023

Good intro to the underlying theory of regression/classification. I'd applied these techniques at a high level before, but I'd never learned how they're actually implemented under the hood.

By Anupam D

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Aug 3, 2022

I like the way jupyter notebooks are designed. It saves time on testing the code because it displays step by step what is happening and allows me to focus on the code logic implementation.

By Gabriel T

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Aug 3, 2022

Amazing course explaining the math behind the most famous algorithm. Good explanation of the gradient descent.

Thank you to Andrew Ng and his team! A bit of math background is needed though

By TC G

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Feb 16, 2024

Sufficiently in-depth to grasp the basics and do a bit of coding. Would have preferred more coding practice within the module, but most people will probably find it difficult enough as is.

By Trung K N

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Nov 19, 2023

Love the way the course was organised , passionate teacher , amazing content 10/10 , though the assigment can be implemented in a more efficient way but overall it was too good of a course

By Max L

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Jul 16, 2023

Exceptionally well-constructed course material with excellent demonstrations. Definitely had a fabulous experience with the content. It was easy to understand but elegant. Enjoyed a lot!!!

By Harshan S

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Jul 6, 2023

Thats really an amazing course to start with for a machine learning career, the course was really easy to understand and explained everything with great detail in a simpler and easier way.

By Elham R

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Aug 20, 2022

I really enjoyed taking this course. I absolutely loved the labs which were very helpful to test my understanding of the material I had just learned. Thank you to Coursera for this course!

By Vinod N

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Aug 9, 2022

Goes into the details of Logistic regression & Classification. The course is designed in a very simple and easy to understand format and Andrew sir is amazing all through out the sessions.

By Amit P

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Jun 9, 2024

A well planned and systematic course to get you in touch with a class of Supervised Machine learning, the labs are quite useful and helps in better understanding of the topics along with.

By Nur M H

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Mar 26, 2023

Amazingly delivered course! Very impressed. A superb educator, Andrew Ng. Using simple to understand examples, he thoroughly described every topic covered in the course. Sir, many thanks.

By Mustafa ö

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Jul 25, 2024

I had a hesitation about the course being too simple or lacking the coding examples and experiences but I was wrong, and I am definitely going for the next course, keep up the good work!

By TUBUN J

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Jul 30, 2023

Mr. Andrew is my favourite ML teacher ever i meet. Thanks for giving me the clear knowledge about the ML as well as the way of teaching.

At last thanks for helping me in my financial aid.

By Pratham D

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Jul 25, 2023

All you need is a good teacher before taking this course I thought machine learning is not my cup of tea . I am really glad I took this course best decision I have ever taken in my life.

By Florian W

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Jul 10, 2022

Great course! I enjoyed it a lot. The pace was good and the labs were a lot of fun. I really enjoyed the interactive jupyter notebooks to play around with in order to get more intuition.

By SERGIO A C

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Jul 7, 2023

I really like to do the details. When coding you need to go to the last detail of implementation. A program that almost run and almost ready ...doesnt work. It does work when is running

By Ivo M

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May 21, 2023

One on the best instructional series I've ever seen - not only in the field of ML, but generally. The lectures and labs are perfectly balanced and allow for gradual and stable progress.

By mutuku n

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May 9, 2023

Lambent is an understatement. I thought it was difficult but it is not. Anyone can go through it. I am looking forward to completing 2 and 3 and later shift to tensorflow specialization

By Tordiah A

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Feb 20, 2023

I MUST CONFESS THAT I HAVE NOT ONLY UNDERSTOOD THE COURSE BUT I REALLY ENJOYED IT TOO.

THIS IS A COURSE WORTH ITS PRICE. THANKS TO EVERYONE WHO CONTRIBUTED TO ITS ESTABLISMENT.

THANK YOU.