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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
18,061 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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51 - 75 of 3,770 Reviews for Supervised Machine Learning: Regression and Classification

By Amelia H B

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Nov 6, 2023

It helped me clarify many confusions I had, I am no longer left with doubts, I can now make my own models, and I am very grateful. Professor Andrew is very clear with the concepts, and I don't even know mathematics, but I know what I have to do :) thanks!!!

By Pritam D

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Jun 30, 2022

Perfect balance of application and theory, and wise choices in ramping up the complexity gradually. Discussion boards are very helpful, feels very much like personalized learning. Thank you!

By Dan C

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Jun 23, 2022

Excellent course, very logical and well structured. Highly recommended to anyone interested in learning about this topic. Assignments are on the easy side but you learn a lot nonetheless.

By Vishnu V

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Jul 24, 2022

This was a great course to understand all the math and logic that goes behind some of the most commonly used ML algorithms. Interesting and a great start to the specialization.

By Reshendren N

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Nov 7, 2023

The course was brilliant and it presented very important ideas in a simple and easy to follow way. The depth and implications of the knowledge presented is quite profound.

By Ryan M

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Jun 25, 2022

Good for beginners. If you have taken the previous online course 'Machine Learning' taught by Prof. Andrew Ng, you may find this course much easier.

By Mohammed A B

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Jul 24, 2022

One of the best ML courses so far. The Course is well designed and very well presented by Andrew NG. I highly recommend it.

By Abhishek P

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Jun 20, 2022

Precise explanation of the fundamentals of Machine learning techniques, using mathematical examples and python.

By 马镓浚

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Aug 7, 2022

Very friendly for beginners, a good refresher if you already had the knowledge of machine learning.

By Alexander S

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Jun 17, 2022

- Amazing instructor

- Very clear and easy to understand examples

By Sayak M

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Mar 20, 2023

Great Great Great Course. Thank you for this amazing course

By Mohammad A V

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Oct 17, 2023

With all these jupyter-notebook labs its fantastic!

By Kahouli M

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Jul 24, 2022

ilove how simple and rich this course is

By Yu L

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Jul 29, 2022

Very clear and intuitive explanation with a great instructor, though the contents are a little too easy, especially for people with a STEM background. More exercise could be set with less guidance (currently it's like writing ten lines of codes for every week of learning). Also, it would be nice if there could be an exercise dedicated to the use of packages like scikit-learn in depth, since that is what most people will end up using the most.

By Kostas M

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Jul 5, 2022

A very good introduction to Machine Learning. I would prefer some more math since this gives me more confidence in understanding, but the course is aimed to a wide audience so that's acceptable. I accompanied the course with Andrew Ng's notes on machine learning.

By Gariman S

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Jul 11, 2022

Andrew sir's teaching made the course interesting and exciting. However, the course was too easy and some more mathematically oriented discussions could have been done.

By Preyas H

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Nov 7, 2023

A good intro to ML. Strikes a good balance of the theoretical and practical aspects of Supervised ML.

By Mubeen u h

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Aug 2, 2022

very good course

By Anudeep P

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Sep 30, 2022

iIt was my frist machine learning course , learned many concepts and this course created more interest in learning advanced algorithms and explore much more concepts

By Mohd A H

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Dec 14, 2022

It is a good course for complete beginners, but for those who want to know things in detail, this course just doesn't quite cut it. It skips the details too much.

By Katie S

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Sep 28, 2022

I was expecting something more challenging and more in depth

By Manish M

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Sep 17, 2023

Programming assignment not giving proper explanation for failure

By Azzam A

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Mar 28, 2023

there are many mistake i hope you solve it ...it loss my time

By Miller R

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May 25, 2023

no refund on 5.24 when last payment is 5.20

By Tavish S N

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Aug 13, 2023

shit-ass course.