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
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

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:

4526 - 4550 of 4,788 Reviews for Supervised Machine Learning: Regression and Classification

By Manasvini G

•

Nov 1, 2024

Loved the way instructor Andrew Ng delivered the concept. Practical knowledge can be poured more.

By Marc A

•

Jun 5, 2024

The labs are not very challenging, maybe some more coding would help to understand more material.

By Oliver M

•

Nov 21, 2022

The derivations of some of the algorithms could have been covered, just for better understanding.

By Alankrit R

•

Apr 25, 2024

this course lacks a little bit in explaining the python implementation of the concepts taught.

By Hammad R

•

Aug 28, 2023

The course teacher has the same tone all over the course hence makes me fall asleep and tired.

By Bisa V

•

Oct 17, 2022

Really very easy to learn and the professor also explained the concepts from the basic level.

By Stephen T

•

Jun 25, 2024

Useful introduction to Supervised Machine Learning, including Linear and Logistic Regression

By jaasim m

•

Feb 27, 2024

the transition from basic to advanced could be more gradual.but the classes are really good.

By Yash S

•

Jan 24, 2024

Well designed and well explained. The coding assignments and optional labs were also great.

By Sharif R

•

Oct 5, 2024

This was the most easily understanding course. Making the tough topics of ML in easy words

By Mohammad F K

•

May 29, 2024

So much details about each and everything. A very fine way of teaching. Thanks Sir Andrew!

By David I

•

Dec 7, 2022

The course is great. I would prefer for there to be more coding involved from the student.

By Alberto C

•

Oct 14, 2024

Great course, it would have been even better to have more practical questions to work on.

By Mauro M

•

Apr 24, 2024

Very good course. Explanations are clear. Exercises could be a little bit more extensive.

By Anandi S

•

Feb 23, 2023

The explanation was pretty clear however, the code should be explained by the instructor.

By Hudhaifa I I G

•

Jan 1, 2023

it was nice course with hands on lab and extensive visualizing for mathematical concepts

By Yohan D A

•

Nov 5, 2024

Super bueno, aunque tiene algunos errores en el codigo, de los laboratorios evalutivos.

By Asnan P

•

Jul 8, 2024

its very good class, everything is very good by need some practical it may be excellent

By Raayan D

•

May 26, 2023

A good introduction. Wish it wasn't so hand-wavy with the math. The labs are very easy.

By Srivaths G

•

Oct 5, 2022

Lovely explaination by the proffessor , the flow and chronology was absolutely perfect

By Reza A

•

Jul 30, 2022

All the lectures are good. The only thing could be better is the assignments exercises.

By Purva T

•

Nov 29, 2023

Andrew Ng has explained every topic in depth and all lectures are easy to understand.

By SREEHARSH N

•

Jun 11, 2023

Great course for those who are looking to step into the world of machine learning!!!

By Rameshbabu

•

May 8, 2023

Great Training. Suggest to add one additional lectures to brush up the mathematics.

By Shashank A

•

Sep 13, 2024

The last portion(logistic regression) looks a bit rushed than the linear regression