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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

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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.

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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4751 - 4775 of 4,966 Reviews for Supervised Machine Learning: Regression and Classification

By Lukman K

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Jan 13, 2023

It gave me the fundamental building blocks of Machine Learning.

By Biswadeep M

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Aug 2, 2024

very good course for developing the basics of machine learning

By Tejas P

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Oct 31, 2023

could include data preprocessing , data cleaning , null values

By Faizan T

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Jun 23, 2022

Vectorized implementation in the assignments would have helped

By Prestigebeetle

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Aug 5, 2023

the course was excellent but it lacked actual implementation.

By Sanjay K

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Jun 23, 2023

This course gives me a lot of idea about ML and other stuffs

By Arwa A

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Mar 30, 2024

great explaining but need to explain coding more than this

By Abhishek_Pandey_IITK

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Aug 30, 2023

A nice and wonderful course.

Bounds you from start till end

By Luca B

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May 14, 2023

Interesting course, not too heavy but direct to the point.

By Shravan D

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Aug 25, 2024

may be a bit more mathematics is required to be explained

By Wassim R

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Apr 18, 2023

I hope to find some obligatory labs (20-30% for example).

By Vishesh D

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Aug 21, 2024

Great experience with my very first course on ML and AI!

By Aryan G

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Sep 4, 2022

the optional lab code should be explained in the videos

By V

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Jul 1, 2022

More graded lab sessions could be included. Good course.

By Omkar D

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Jul 20, 2024

requires more practice lab, content is great thank you

By Moisés M B R R

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Oct 25, 2022

Great for those looking to get into Machine Learning.

By Mahesh R

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Jan 3, 2025

It was super , but i think i need even more practice

By Mubbara M

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Dec 5, 2024

This course is good for developing your basics in ML.

By Holmes

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Jul 3, 2023

A little bit overwhelming in the last lab. I love it.

By Janardhan P

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Mar 9, 2024

Good explanation. ButI expected more deep knowledge.

By Tobias H

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Jan 29, 2023

Very rough overview. But good entrance level lecture

By Francisco A S

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Sep 30, 2022

Lacks coding , but its very nice in terms of theory

By Jeyanth (

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Aug 5, 2022

the coding part could have been explained in detail.

By Aniruddh L

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Jul 12, 2022

Graded Assignments were slightly on the easier side.

By Jayanth S

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Aug 8, 2024

Helps to understand the intuition behind the model.