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

4.9
stars
25,380 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

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.

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.

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3151 - 3175 of 4,970 Reviews for Supervised Machine Learning: Regression and Classification

By Talha K

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Sep 7, 2022

Concise. Efficient. Beginner Friendly

By Mohamed O

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Aug 25, 2022

very good course, and well organized.

By Kishore I

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Aug 15, 2022

Excellent introductory course on ML.

By emirhan e

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Aug 7, 2022

Thanks for this precious oppurtinity.

By Carlo D

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Jul 26, 2022

best intro course to machine learning

By Anush R A

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Jul 12, 2022

best course to learn machine learning

By Daniel A

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Jul 11, 2022

Course very well executed. Thank you.

By Sayed M

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Jul 10, 2022

Thank you all for this amazing Course

By 黄金

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Jul 6, 2022

The lab part of the course is amazing

By Yuhao W

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Jul 4, 2022

better than before, with python coded

By Gorgui B M

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Jul 1, 2022

Great professor and exellent content!

By Henrik S

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Jun 27, 2022

It was everything I wanted it to be!

By Luke T

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Dec 29, 2024

Beautifully explained and delivered!

By Mohammad J S

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Dec 11, 2024

perfect course I have had this year.

By Shaik M

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Jun 25, 2024

Andrew Ng is god of machine learning

By Ashirvad P

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Jun 18, 2024

Good Course ! I personally enjoy it.

By Gaurav P

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May 19, 2024

Really giving thorough understanding

By Tanuj S

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Feb 12, 2024

Great course! Thank you to Andrew Ng

By Jaroslaw K

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Jan 27, 2024

Easy to understand with helpful labs

By Gokul A

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Jan 13, 2024

One of best and correct paced course

By Sahan L

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Jan 13, 2024

Excellent and very inspiring course.

By Tanvir A S

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Dec 20, 2023

A wonderful course making ML easier.

By Emre G

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Oct 9, 2023

amazing course, had amazing insights

By Seyed K M Z

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Sep 7, 2023

a great course to start learning ML!

By ekins K

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Aug 4, 2023

Excellent course, beginner friendly.