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

4.9
stars
24,299 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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751 - 775 of 4,791 Reviews for Supervised Machine Learning: Regression and Classification

By VILAS S

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Sep 25, 2024

I have been glad to be able to cover this course through financial aid, looking forward to complete this course and be a part of the machine learning, thanks Andrew NG for providing such a amazing course

By Abdul A N

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Feb 4, 2024

Now I have a solid grasp of Regression, Classification, and Gradient Descent. Andrew expertly untangled the complexities and turned what seemed complicated into a comprehensible gem. Thank You very much!

By Rifat A E S

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Jul 29, 2023

Really amazed to learn how the modern advancement of AI and Machine Learning are build with pure mathematics and statistics. Great thanks to Andrew Ng for making these complex concept easy to understand.

By Surasin T

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Aug 21, 2022

This improved version is a lot easier to follow comparing with 3 years ago.

The course has been designed very well. No software installation is required. The couse is using an online tool to do the labs.

By Noel T

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Jul 30, 2024

Goes over the core fundamentals of Machine Learning. Motivated me to go through the course taught by Dr. Andrew NG at Stanford from YT in parallel to support the learning experience, was super worth it!

By Ghulam M

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Jul 10, 2024

This course provided a comprehensive and hands-on introduction to supervised machine learning, equipping me with the skills to tackle real-world regression and classification challenges with confidence!

By Mirro S

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Oct 23, 2023

Absolutely brilliant course. Self taught enginner, wanted to learn more about building tools with ML and this course really gave me the fundemental knowledge I needed to take the next leap in my career.

By Hendri T

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Mar 31, 2023

The instructor has a deep understanding about Supervised Machine Learning and communicate/explain it very well in the video. The Labs are also useful to understand how to implement the theory into code.

By manobharathi m

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Mar 18, 2023

Amazing course, I recommend who want to deep dive in Machine Learning should enrol in this course.

This course is designed for all the people but you need to understand python code to practice algorithms

By sohith k

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Oct 30, 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 .

By Katerina A

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Jul 28, 2022

It was the best course I ever had! It iwill be very difficult for me to use the algorithms I was tought, but I am very thrilled that I finished it! I am grateful to Professor Andrew Ng and the team!!!!

By Goitom Y

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May 1, 2024

"Supervised Machine Learning: Regression and Classification" is an excellent introductory course that effectively teaches the core concepts and provides practical experience through coding assignments.

By Asfaw G

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Jun 10, 2023

I loved this course a lot. The environment, the teaching methodology, the follow of concepts... everything is well crafted. And I can't thank you enough for availing this amazing course free of charge.

By Anand S

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May 9, 2023

Has to be the best course in ML I have ever taken. Thanks to Coursera for the Financial aid. I would recommend the course for anyone who wants to learn the basics of ML in a fun and interactive manner.

By Javier G

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Apr 27, 2024

Es un curso diferente a los de regresión y clasificación donde solo se enfocan en aplicar los algoritmos de Scikit-learn. El profesor Andrew le da un enfoque profundo al detrás que hay en cada modelo.

By Sebastian A

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Aug 9, 2022

I really liked it! Andrew explained perfectly all the concepts and I understood everything.

The only thing I think It could improve is to have more Lab Tests, so you practice more what you have learnt.

By Mohd A

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Sep 18, 2024

I learned a lot from this specialized course. It was one of the best courses that I've ever done. The instructor i.e. Andrew Ng taught every concepts so well. I'll highly recommend others to do this.

By Susanne B

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Nov 6, 2022

This course is a brief but thorough introduction. It has a good mixture of theory and practice.

Andrew Ng explains every thing very good, understandable and in a fun way.

I highly recommend this class!

By Adrian C

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Oct 8, 2024

great course. Nice explanation even if you are not familiar with certain mathematical concepts Like Gradient. I would recommend having some mathematical base to ease the understanding of the course.

By renaisan g

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Aug 31, 2024

The course was excellent, and I gained valuable knowledge throughout. I am also grateful for the financial aid, which allowed me to complete the program successfully. Thank you for this opportunity.

By Abdullah-Al M

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Mar 11, 2024

This course has offered invaluable insights and clarity in understanding machine learning concepts. It was a nice journey towards understanding practical application and complex concepts made easy.

By Rizwan N T

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Apr 13, 2023

it is probably one of the best courses i've ever taken, definitely recommend for beginners, and then to further improve your skills, take the other 2 courses of the specialization, i will do so too

By Fahad M

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Sep 23, 2022

Very Engaging course. The instructor explains stuff in a way such that a student can develop a sound intuition of the mathematics behind the algorithms in addition to the implementation side of it

By Anuj P

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Sep 3, 2022

A perfect course for beginners who are seeking to learn machine learning. I want to thank Mr. Andrew Ng and his team for this wonderful course. Thank you so much for providing this quality course.

By João V B

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Aug 19, 2022

It's a very comprehensive course for beginners. Like others said, I believe it best if the person knows some basic Python and algebra for this, as they'll be able to better understand the lectures.