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返回到 Supervised Machine Learning: Regression and Classification

学生对 DeepLearning.AI 提供的 Supervised Machine Learning: Regression and Classification 的评价和反馈

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31,037 个评分

课程概述

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....

热门审阅

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.

JG

Apr 26, 2024

Es un curso diferente a los de regresión y clasificación donde solo se enfocan en aplicar los algoritmos de Scikit-learn. El profesor Andrew le da un enfoque profundo al detrás que hay en cada modelo.

筛选依据：

5851 - Supervised Machine Learning: Regression and Classification 的 5875 个评论（共 5,913 个）

创建者 Muhammad U A

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May 21, 2025

kind a slow and not interesting

创建者 Josep B P

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Dec 30, 2023

Step down from the old course.

创建者 NITHISH K

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Jun 29, 2025

the recorded video looks old

创建者 Islam I

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Nov 8, 2024

Concept Only no Beyond that

创建者 Sepehr

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Mar 7, 2024

Easy to follow but useful.

创建者 Fernando B

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Oct 23, 2023

Laboratórios muito básicos

创建者 Aravind N

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Jun 6, 2024

Could cover more concepts

创建者 Kotulski G

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Aug 5, 2024

Not enough practice quiz

创建者 Tanishka G

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Jun 18, 2025

GOOOOOD COURSE

创建者 Harsh S

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Jun 15, 2023

average course

创建者 Biswaraj

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Jul 3, 2024

quite good

创建者 Donia A R A

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Jul 16, 2022

Excellent

创建者 vivek N

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Aug 31, 2024

ok ok ok

创建者 Krishna S

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May 21, 2024

too fast

创建者 Kushagra G

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Oct 14, 2024

decent

创建者 Eman E

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Feb 9, 2024

good

创建者 Mahesh G

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Aug 21, 2023

s

创建者 Gayatri P

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Nov 11, 2025

The coding part wasn't really taught at all. The professor explained the mathematical concepts well but i was also expecting to actually learn the coding from scratch

创建者 Rohith K

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Nov 24, 2025

the preatice lab is not correct it has error i am not able crt those error because the lab is not able to write the code

创建者 Richie B

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Nov 29, 2022

Great course if you know how to program, but you really need a python background to appreciate it.

创建者 Daniele d b

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Dec 14, 2023

quite too basics...too few practical exercise, just scratching the surface of ML

创建者 rverker

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Jun 23, 2024

Impossible to do the exercises if you don't pay. The course is interesting.

创建者 Rohan S

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Jun 2, 2025

The course should have mentioned that Python knowledge is a prerequisite.

创建者 Juergen G

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Aug 15, 2023

Very nice and helpful for my next career steps.

创建者 Anish I

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Jan 29, 2024

too theoretical, not much hands on learning