糖心vlog官网观看

Chevron Left
Back to Supervised Machine Learning: Regression and Classification

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

4.9
stars
30,880 ratings

About the Course

In the first course of the Machine Learning Specialization, you will: 鈥 Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. 鈥 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鈥檚 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鈥檙e 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.

Filter by:

1776 - 1800 of 5,846 Reviews for Supervised Machine Learning: Regression and Classification

By Abhijeet G

May 30, 2023

Very much helpful for beginners. Concepts are explained in a very detailed way. Also, all labs are beneficial.

By Liam W

Oct 11, 2022

Very helpful for someone wanting to understand the basics of machine learning without going too much in depth

By Nirmala R

Aug 18, 2022

Crisp videos and very nice illustrations! Implementing gradient descent really helps understand the algorithm.

By omar a

Sep 13, 2025

One of the best courses i have seen, andrew was very clear, and provided the theorical foundations very well.

By Sukrat S

May 11, 2025

Very great course, explained each topic in a simplifies manner along with code implementations. Helped a lot!

By Tamara C

Nov 9, 2024

Las explicaciones del temario son sublimes, muy cercanas y visuales. La aplicaci贸n en Python, muy did谩ctica.

By Rola I

Sep 21, 2024

丕賱丿賵乇丞 乇丕卅毓丞 噩丿丕 賵 賲賮賷丿丞 貙 賱賯丿 賯賲鬲 亘鬲毓賱賲 丕賱賰孬賷乇 賲賳 丕賱兀卮賷丕亍 丕賱噩丿賷丿丞 賵 丕賱賲賮賷丿丞 賮賷 丕賳卮丕亍 賲卮丕乇賷毓 ML 貙 卮賰乇丕 乇賵賱丕

By Darmen M

Jul 25, 2024

Very beginner friendly course. Experienced learners may view at 1.25-1.5x video speed. Overall, great course!

By Yu Y

Feb 11, 2024

A clear a thorough introduction to ML. Accessible to anyone with basics of mathmatics and programming or not!

By Leonid H

Dec 28, 2023

Excellent course for beginners, but you must have knowledge of engineering mathematics to facilitate learning

By Lucas D

Oct 14, 2023

Going from very simple ideas to advanced math concepts smoothly, I really enjoyed Andrew' pedagogical skills!

By Nina G

Sep 1, 2023

Very beginner friendly but with enough detail to keep those with more math and programming experience engaged

By Mashrur K

Jul 15, 2023

I rated this course a five, but only as a excellent pre-requisites (area) to other, even more advanced topics

By Nayan D

Mar 21, 2023

Really great course for diving into the world of Machine Learning. Excellent explanations. Great online labs.

By Aashit A

Dec 22, 2022

Andrew NG explained the machine learning concepts in very simple way, and further looking for the next course

By Hichem M

Oct 17, 2022

Excellent course that combines theoritical and practical aspects for regression and classification problems.

By Vasyl S

Oct 12, 2022

Great. Professional. Comprehensive. Inspiring.

I am also grateful for financial aid to complete this course.

By Aldo G

Aug 1, 2022

It is better than the previous version in octalab, keeping clear explanation and more interactive with Adrew.

By Hieu H T M

Sep 4, 2025

I have learned a ton of things in this course. It help me know more clearly about the path in AI engineering

By shanmukh

Mar 19, 2025

very clear and neat explanation ,even non techie can understand ,extreamly elagant teaching by andrew ng sir

By Irala R

Feb 20, 2025

Absolutely best beginner friendly machine learning course ever!!!! Learned a lot and absolutely recommended.

By S P A K J

Dec 23, 2024

The step by step approach of teaching complex concepts in easier straight forward way in progressive manner.

By Luca C

Oct 25, 2024

One of the best courses I have ever taken throught my University career. A must for everyone in this domain.

By Nico T

Oct 6, 2024

Excellent introduction, extremely clear, fantastic visualizations. Highly recommended for absolute beginners

By Aisha U

Jul 4, 2024

This course provided a great foundation for machine learning. A perfect balance between the math and coding.