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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
30,836 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

AA

Apr 30, 2023

Optional Lab lot more time than mentioned without prior experience of python and libraries used. Its estimated time should be change, it's a lot more than 1 hour. Video and exercises are very good.

DB

May 31, 2024

Great intro to supervised learning (regression & classification). Clear explanation of sigmoid function and decision thresholds. Could benefit from examples & exploring non-linear boundaries.

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4651 - 4675 of 5,846 Reviews for Supervised Machine Learning: Regression and Classification

By 韩秀程

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Nov 18, 2024

很棒的入门课程！强力推荐！

By Malak S

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Oct 23, 2024

Great Course!

By Ennouamane K

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Oct 2, 2024

Great course.

By Chitra M G 2

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Sep 2, 2024

good teaching

By Bharath S

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Aug 12, 2024

Well planned.

By Izaias J

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Aug 9, 2024

Just great!!!

By Ronald N

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Aug 7, 2024

Great course.

By Mammad M

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Aug 1, 2024

Great course!

By Chaima B

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Jul 22, 2024

i'm satisfied

By Prof H F

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May 9, 2024

Really good !

By Ankit

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May 2, 2024

great course!

By Liliia E

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Apr 4, 2024

Thanks a lot!

By Alexander J

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Mar 19, 2024

Great course!

By Shivam A

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Mar 15, 2024

Great Course!

By Vidyut K

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Jan 31, 2024

Nicely taught

By Dimitrios - M A

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Jan 29, 2024

Great course!

By nguyen t t

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Jan 6, 2024

nice and good

By Sabeur M

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Dec 21, 2023

Great courses

By Mehdi K

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Nov 11, 2023

perfecttttttt

By Imam U

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Oct 21, 2023

Great for all

By Aditya T

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Oct 7, 2023

v good course

By Liam B

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Aug 29, 2023

Great Course!

By Yoann S

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Aug 12, 2023

Great course!

By Ashwin R

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Jul 18, 2023

Great course!

By Anush R

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Jul 18, 2023

Superb course