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

4.9
stars
18,827 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

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.

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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3851 - 3875 of 3,892 Reviews for Supervised Machine Learning: Regression and Classification

By Jack B

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Jul 14, 2023

Much more of the lesson content needs to be focused on the code, rather than the underlying maths, seeing as it is purely code which is assessed.

By Rob I

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Jun 12, 2023

Love the trainer. Would have been nice to start coding earlier. By the time we were called to actually write code, it was way too late.

By eklektek

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Jul 20, 2022

Doesn't really enable "DeepUnderstanding" - all abit rushed. Spend time afterwards going through more examples with more rigor.

By Rollie O K

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Sep 20, 2023

Had problems with Python. I does so much for you it sometimes makes it difficult for a C, C++ or Java programer

By Hosein F

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Oct 20, 2022

Lectures were very clear and smoothly explained but the discussed consepts were only for complete begginers.

By Muhammad B

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Dec 4, 2023

Thank you sir . I learned many new things from this course which will help me to much in my research work..

By Xander N

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Oct 18, 2023

Lot of great learning, but not taking into account using a lot of newer open source options.

By Daniel S

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Apr 12, 2024

A bit long winded for problems that can be solved with 1-2 lines of code

By A A

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Mar 16, 2024

the course lacked the many beginner things and was slow enough for me

By Abdallah A

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Jan 6, 2024

The coding parts are not easy to understand on your own as a beginner

By Hardik D

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Mar 2, 2023

3 and half. I wish the course was designed to get us to code more.

By Yuliya A

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Mar 8, 2024

Instructor is wonderful but course structure can use improvement

By Ganesh K

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Jul 26, 2023

Course is good but lab assignments and exercises are less.

By shivam s

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Feb 26, 2023

Should also some small projects for better understanding!

By Mohamed a a

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Jul 23, 2023

good course but i wish it was more project oriented

By kunal s

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Jun 12, 2023

please include projects in this course.

By Boris A

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May 26, 2023

A lot of theory and a bit of practice

By Josep B P

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Dec 30, 2023

Step down from the old course.

By Sepehr

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Mar 7, 2024

Easy to follow but useful.

By Fernando B

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Oct 23, 2023

Laboratórios muito básicos

By Harsh S

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Jun 16, 2023

average course

By Donia A R A

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Jul 16, 2022

Excellent

By Eman E

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Feb 9, 2024

good

By Mahesh G

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Aug 22, 2023

s

By Roman K

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Feb 29, 2024

I passed the "Machine Learning" course by Andrew NG in 2019, and I took this course as a part of my specialization. So this course looks like a simplified and cut version of its predecessor. Most of the Lab files are not downloadable as PDFs, so, after the course finishes - you can't have that data with you. Quizzes are so much oversimplified, like 2 questions, I think in the previous course it was much harder and it took me time to learn things. This review is a bit chaotic, I am sorry for that. I know that Andrew Ng is a great teacher, and in the previous course, he gave so much more valuable information and the simplification of that course makes me sad.