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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

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.

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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4651 - 4675 of 4,718 Reviews for Supervised Machine Learning: Regression and Classification

By Arvin G

•

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

•

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

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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 Phil N

•

Jun 26, 2024

This course requires Python programming experience using the libraries this course needs. It is not suitable for learners with basic coding experience.

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 Seyyed F A N

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Jun 23, 2024

The videos were really helpful, but the optional labs were useless. Besides, the practice labs felt like you are jumping few steps.

By eklektek

•

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

•

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

•

Oct 20, 2022

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

By Muhammad B

•

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 Mark S

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Sep 4, 2024

Good for absolute beginners with no background. Too slow and peace-meal information for anyone else.

By karthik k

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Oct 11, 2024

The explanation of the theory is good, but there is no explanation at all when it comes to coding

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 SACHIN I

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May 26, 2024

Everything mostly taught was theory.I learnt very few concepts of coding.Disappointed!!

By Arnab B

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Jun 23, 2024

Theory part is good but the practical coding part is not much interactive

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

•

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

•

Mar 8, 2024

Instructor is wonderful but course structure can use improvement

By Yesid J

•

Jul 14, 2024

Esperaba ver un curso más práctico, pero fue demasiado teórico.

By Ganesh K

•

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 Faezeh T

•

Sep 25, 2024

it would be better if there were more coding experiment.