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学生对 DeepLearning.AI 提供的 Advanced Learning Algorithms 的评价和反馈

4.9
8,311 个评分

课程概述

In the second course of the Machine Learning Specialization, you will: • Build and train a neural network with TensorFlow to perform multi-class classification • Apply best practices for machine learning development so that your models generalize to data and tasks in the real world • Build and use decision trees and tree ensemble methods, including random forests and boosted trees 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 theoretical 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....

热门审阅

DG

Apr 14, 2023

Extremely educational with great examples. Helpful to know Python beforehand or the syntax will become a time sync, and understanding the mathematics as going through the class makes it a decent pace.

MA

Jun 21, 2025

The course is well crafted and enriched with deep learning and ensemble tree knowledge. Practice labs add strength to the development of skills. Overall good learning experience under sir Andrew NG.

筛选依据:

726 - Advanced Learning Algorithms 的 750 个评论(共 1,243 个)

创建者 Nafiz s

Jan 24, 2023

This was an great course by Andrew NG.

创建者 Anupam

Oct 20, 2022

Excellent way of teaching. Thank you!

创建者 Philip G

Aug 15, 2022

really good and highly recommendable.

创建者 Jan S

Aug 8, 2022

An amazing introduction to the subject

创建者 Mohd U

Oct 18, 2024

its been awesome to learn from andrew

创建者 Abdullah A

Jun 29, 2024

Mr. Andrew is an excellent instructor

创建者 sriraj p

Jan 22, 2024

Best course to strengthen your basics

创建者 Shruthi B K

Nov 15, 2023

It was comprehensive and well taught.

创建者 Karan P

Jun 17, 2023

Very Insightful and nicely expalined.

创建者 Victor T

Sep 28, 2025

Excelent way to explain all concepts

创建者 Hrishikesh K

May 12, 2024

Very well structured and I loved it.

创建者 Rajasekhar B

Apr 14, 2024

Andy’s teaching skills are awesome!!

创建者 Priyanshu P

Jan 25, 2024

amazing course, thank you so much!!!

创建者 Bruno R

Dec 4, 2022

Best course on internet, thanks all!

创建者 ehsan k

Oct 16, 2022

Simply the best! Thank you Coursera

创建者 Shivam V

Oct 14, 2022

Good one, gain a lot of information

创建者 Kohila B

Aug 14, 2025

Excellent explanation by Andrew Ng.

创建者 Tejash T

Jun 15, 2025

Very useful and informative for me.

创建者 adrian c

Jun 7, 2025

Impressed by how much I've learned!

创建者 RUSHI P

Apr 13, 2025

Gained Amazing Conceptual Knowledge

创建者 Alex T

Feb 18, 2025

Good, simple for understanding info

创建者 Shakil H 2

Nov 22, 2024

It was so difficult for me to learn

创建者 Fabio A T

Nov 20, 2024

super Teacher and very good course.

创建者 Pavol D

Jul 8, 2024

Awesome as every course from Andrew

创建者 Tùng N

Oct 11, 2023

love it, May the Forest be with you