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

4.9
stars
18,061 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.

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

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601 - 625 of 3,773 Reviews for Supervised Machine Learning: Regression and Classification

By José Á A B

Dec 15, 2022

It is amazing how complex concepts and equations were taught in very simple and pertinent ways, stating at every step which understandings were essential and which weren't, etc. Overall, an excellent course.

By Deleted A

Nov 13, 2022

Detailed explanations were excellent. I was able to follow them and get an true understanding of some very powerful ML techniques. Quizzes were just right. Code examples and assignments were very well done.

By Anton

Aug 1, 2022

Great course for complete beginners. I would recommend something different for people with technical backgrounds though - this one is too simple (although I do understand that it is not a bug, but a feature)

By Ashraf H

Jun 26, 2022

It was a great learning experience! Thanks to Dr. Ng and to everyone who contributed to creating this wonderful course. The content was very accessiable and made learning such a complex subject, quite easy.

By Ittai H R

Nov 21, 2023

I think the course should have videos about coding. This course required a strong foundation in coding. Without prior knowledge of coding, it would have been challenging to successfully complete the course.

By S S R

Sep 22, 2023

The course is really great regarding the theory the implementation part can be more focused on using an existing library such as scikit-learn but overall is was really informative and a 5/5 worth it course.

By Jorge S

Sep 12, 2023

Excellent! Professor Andrew is one of the best professors I have ever seen in the field. He explains in a simple way a lot of complicated maths and statistics concepts, even for non-native English speakers.

By Hetarth J

May 31, 2023

This course builds the fundamentals of Linear and Logistic Regression in a Machine learning enthusiastic student. It gives a great theoretical and practical implementation of Linear and Logistic Regression.

By Indyra O

Apr 13, 2023

I have no prior knowledge in programming and had basic math skills. Even though it went a bit slower then projected, I could still manage to complete this course and understand the core concepts. Thank you!

By Sashka W

Oct 22, 2022

One of the best online courses I have ever taken! Excellent real world examples and clear + logical explanation of concepts in a tangible way. 5 stars - would recommend to everyone interested in the topic.

By Hans-Henrik F

Oct 12, 2022

Andrew Ng is a superb educator, he takes you gently throught the ML basics with strong intuitive reasoning where the math could be hairy for some. This balance is fine and Ng is a master in this fine art!

By Pavlo B

Aug 21, 2022

Simple and practical, the course teaches the basic tools of machine learning, logistic and linear regression. It also touches on feature scaling, under- and overfitting, regularization and gradient descent

By Petro S

Aug 1, 2022

First of all thank you for possibility to study this course.

Material is presented in a clear and understandable way.

The examples presented are clear.

Liked the interactive possibilities of laboratory work.

By Ömer E A

Mar 14, 2024

Best course for beginners. Andrew Ng is an amazing instructor and I am looking forward to start to his other courses. However, even though I definitely learned a lot, I wish this course was a bit harder.

By Hossein H N

Feb 20, 2023

I highly enjoyed the course .special thanks to Andrew for clear and simple teaching during the course. this course pushed me one step closer to the goal. Definitely I will enroll in 2 next course of this

By Aneesh V

Sep 28, 2022

One of the best online course. Even a person with a complete different domain knowldge can successfully complete this course without much dificulty. The math is not deep but to the point. Labs are great.

By Ahmed F

Jul 24, 2022

an amazing hands on experience, you not only learn ML but also python on the go and it is a very amusing course and very short to the point, easy to finish with some little effort and concentration on it.

By Jeff W

Jul 2, 2022

I started taking the old version and then I heard this one was coming, so I did the new one instead. Much better! Great to be in Python and even clearer lectures. Prof Ng is easy and fun to listen too.

By Abdul A N

Feb 4, 2024

Now I have a solid grasp of Regression, Classification, and Gradient Descent. Andrew expertly untangled the complexities and turned what seemed complicated into a comprehensible gem. Thank You very much!

By Rifat A E S

Jul 29, 2023

Really amazed to learn how the modern advancement of AI and Machine Learning are build with pure mathematics and statistics. Great thanks to Andrew Ng for making these complex concept easy to understand.

By Surasin T

Aug 21, 2022

This improved version is a lot easier to follow comparing with 3 years ago.

The course has been designed very well. No software installation is required. The couse is using an online tool to do the labs.

By Mirro S

Oct 23, 2023

Absolutely brilliant course. Self taught enginner, wanted to learn more about building tools with ML and this course really gave me the fundemental knowledge I needed to take the next leap in my career.

By Hendri T

Mar 31, 2023

The instructor has a deep understanding about Supervised Machine Learning and communicate/explain it very well in the video. The Labs are also useful to understand how to implement the theory into code.

By manobharathi m

Mar 18, 2023

Amazing course, I recommend who want to deep dive in Machine Learning should enrol in this course.

This course is designed for all the people but you need to understand python code to practice algorithms

By sohith k

Oct 30, 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 .