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

4.9
stars
24,947 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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1376 - 1400 of 4,876 Reviews for Supervised Machine Learning: Regression and Classification

By mahwiz

Jul 6, 2022

The course has been updated very well, Python makes the tutorials much easier to follow, All of you did an excellent job.

By Mayank B

Nov 22, 2024

Amazing, I would recommend this course to anyone who likes to learn from machine learning from basics to advanced level.

By Gannavarapu G M

Aug 4, 2024

This cource make me interst to learn machine learning"This course has sparked my interest in learning machine learning."

By Shedrach K M

May 23, 2024

It was very informative, Andrew was very detailed and he made it seem easy to understand with his technic in presenting.

By Levent A

Oct 26, 2023

It was a very well sequenced introduction for machine learning algorithms and specializations to specific problem types.

By Reza M

Jul 31, 2023

After passing lots of machine learning courses finally, I can say I have a good grasp of the concepts used in the field.

By Divyansh S

Feb 14, 2023

Great explanation by Professor Andrew Ng along with lovely visualisations of how the changes we make impact the results.

By Nima1313

Feb 11, 2023

Pretty good for starters!

the content was explained masterfully and the labs helped to develop my practical skills a lot.

By Gelli V S G

Oct 9, 2022

This course was great with practical examples. The instructors done a great job by explaining the concepts elaborately.

By Ananthu C V

Aug 24, 2022

A course that explains things incredibly simply to even beginners. Beautiful place to start machine learning algorithms.

By Bharath I

Jul 4, 2022

Very well structured course with very interesting coding assignments. Andrew ng's explainations crystal clear as always.

By marlon

Jun 25, 2022

Excellent. Andrew and his team developed a great introduction, where you can feel comfortable at any level of knowledge.

By 满江涛

Feb 4, 2024

Thanks to Professor Andrew Ng, the course is very friendly for me as a beginner, and I will continue to learn with you!

By Ashwni

Oct 9, 2023

The course has been phenomenal and Dr. Andrew Ng taught the concepts in very lucid manner. Thanks DeepLearning.AI team.

By Chaitanya G

Oct 6, 2023

Amazing Course for Machine Learning for Beginners !! Couldn't believe things can be as intuitive as sir teaches 👏👏👏

By Manal C

Aug 10, 2023

thanks a lot ! It was fun and I learned a lot ! I am looking forward to working with you Andrew in the near future ! :D

By zain u a

Jul 18, 2023

The instructor was very educated and helpful. Hopefully, I will be able to achieve my goals after learning this course.

By Navindi D

Jul 7, 2023

Thank you for explaining the facts in an easy-to-understand manner. I learnt a lot from the talented course instructor.

By Jaswinder P S

May 29, 2023

Very clear instruction which can be instantly put to use. One just needs a feel for matrix - vector operations in numpy

By Omar K

May 25, 2023

Simply Brilliant course from a brilliant tutor. I highly recommend it to anyone who wants to get into machine learning.

By Muhammad A H

Feb 11, 2023

Good course for beginners, who looking to learn machine learning.

Everything was deeply explained by my dear instructor.

By Nishshanka C D S

Dec 25, 2022

I am a beginner in ML and AI. I learned so much valuable things during this course. Thank you very much for the effort.

By Abhay K S

Dec 9, 2022

Exceptional introduction for anyone looking to get their hands wet in the world of ML. No prior coding skills required!

By Yhobany M G

Sep 26, 2022

Andrew Ng es simplemente espectacular para enseñar los conceptos basicos pero determimantes para el Machine Learning.

By Navead J

Sep 1, 2022

Excellent course. I just wish they used more linear algebra and less algebra, but you can figure that out on your own.