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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
18,908 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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3701 - 3725 of 3,908 Reviews for Supervised Machine Learning: Regression and Classification

By Kunal G

•

Aug 16, 2022

Good One, the course is to the point . Please include linear algebra as it was added in the older version .

By Royston L

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Jun 21, 2022

I don't understand why the practice lab code for gradient descent and the lab assignment code is different.

By Fang H

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Jan 23, 2024

Explained the complex concepts in very clear and simple way. Labs are very helpful and very well designed.

By Samuel S

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Jul 16, 2022

It get's exponetially harder as the weeks go by. This course could really use more programming excercises!

By Alzahra A A

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Jul 21, 2023

A great course, very informative and easy to understand.

Wish there were more project based assignments.

By Ryan H

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Jun 29, 2023

Weeks 1 and 2 were great. Week 3 got a little complicated and seemed a bit esoteric... But very happy.

By Sai D N

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Jul 12, 2022

It an introduction to ML. Course flow is fantastic and assignments are important to learn the content.

By Nikhil J

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Sep 5, 2022

It is a nice course , from this i learned what is regression and classifications in machine learning

By Nikita

•

Jun 13, 2023

I wish there were more practice tasks. But this course gives you good understanding of the concepts.

By Ans S

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Mar 29, 2024

Best for learning deep concepts and mathematics inside but not sufficient for the job ready skills.

By Oliver M

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Nov 21, 2022

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

By Alankrit R

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Apr 25, 2024

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

By Hammad R

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Aug 28, 2023

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

By Bisa V

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Oct 17, 2022

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

By Muhammed J K

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Feb 27, 2024

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

By Yash S

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Jan 24, 2024

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

By Deep

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Aug 30, 2023

If some small project type of stuffs are added in the course, that would be more of a help.

By David I

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Dec 7, 2022

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

By Mauro M

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Apr 24, 2024

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

By Anandi S

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Feb 23, 2023

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

By Hudhaifa I I G

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Jan 1, 2023

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

By Raayan D

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May 26, 2023

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

By Srivaths G

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Oct 5, 2022

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

By Reza A

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Jul 30, 2022

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

By Purva T

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Nov 29, 2023

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