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

4.9
stars
18,868 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

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.

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3851 - 3875 of 3,899 Reviews for Supervised Machine Learning: Regression and Classification

By Parsa G

•

Mar 2, 2024

it was a really great theorical course but the practical parts were too small. so I know alot about the concepts and I can calculate stuff but i can not implement them that much , and I'd rather the course to have more difiicult math! well done!

By Jorge M

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Feb 28, 2023

It is really interesting, I think I have miss more focus on connecting everything together from the function f_wb to cost function to deltas to preditions. The labs are not very challenging.

By J.P B

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Mar 29, 2024

Code cannot be transferred easily to jupyter notebooks or google colab. The course was 90% theory. Needs more real-world practice and projects. Other than that Theory was very good.

By Arvin G

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Dec 6, 2022

the course is well structured and you'll gain the fundamentals of ML. But the practical labs should be more challenging in my opinion. I am looking forward to the next course.

By Sourabh P

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Mar 12, 2023

There is very less practice content for students. I hope keeping more graded notebooks would be helpful for students to get more practice and understand the concepts better.

By Antonio G

•

Dec 10, 2022

The course is interesting but focuses on very theoretical aspects, more suited to academia than the working world. Unfortunately, the audio is not the best.

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

•

Feb 26, 2023

Should also some small projects for better understanding!

By Mohamed a a

•

Jul 23, 2023

good course but i wish it was more project oriented

By kunal s

•

Jun 12, 2023

please include projects in this course.

By Boris A

•

May 26, 2023

A lot of theory and a bit of practice

By Josep B P

•

Dec 30, 2023

Step down from the old course.

By Sepehr

•

Mar 7, 2024

Easy to follow but useful.