Chevron Left
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.

Filter by:

3251 - 3275 of 4,720 Reviews for Supervised Machine Learning: Regression and Classification

By DUY D

•

Dec 18, 2023

great course, easy understand

By Youwei Z

•

Nov 24, 2023

fundamentals are truly great.

By yoss n

•

Oct 26, 2023

super amazing! Thanks andrew!

By Cay D

•

Sep 8, 2023

Great machine learning course

By C S J

•

Jul 5, 2023

andrew neg is a great teacher

By Ayush S

•

Jun 14, 2023

Outstanding teaching loved it

By Noman S

•

Apr 16, 2023

Very good method of teaching.

By Harsh V T

•

Mar 25, 2023

best course I have ever done

By 19 徐 徐

•

Mar 21, 2023

非常豐富的基礎機械學習內容，就算非本科系的人也很容易理解。

By JANA A A A

•

Mar 15, 2023

i really enjoyed learning SML

By Miao H

•

Jan 30, 2023

Very interesting and helpful!

By Agustin N

•

Jan 28, 2023

Very good! Clear explanations

By Nuno D C

•

Jan 2, 2023

A well and thought out course

By Karthik P

•

Dec 14, 2022

Great for building foundation

By Clément N

•

Nov 9, 2022

This course was just perfect!

By AABID I S

•

Oct 19, 2022

awresome course by andrew ng

By Saurabh T

•

Oct 10, 2022

Very informative and helpful

By Ale S

•

Aug 24, 2022

Andrew Ng is the best teacher

By Mahmoud A

•

Jul 24, 2022

One Of The Best Courses Ever

By Janice C

•

Jul 2, 2022

Prefect course for beginners

By 张涵茗

•

Oct 19, 2024

best ML course of the world!

By Babak A

•

Oct 10, 2024

Easy, basic, and fundamental

By Amit A

•

Sep 13, 2024

Taught in best possible way.

By Amruta G S

•

Jun 21, 2024

very deep and understandable

By Bison

•

Jun 1, 2024

Just thankful for everything