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

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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

AA

Apr 29, 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 30, 2024

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

筛选依据：

5026 - Supervised Machine Learning: Regression and Classification 的 5050 个评论（共 5,928 个）

创建者 Jomarie O

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Oct 25, 2023

very nice

创建者 Zanko Z

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Oct 13, 2023

Excellent

创建者 Siddharth M

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Oct 6, 2023

Excellent

创建者 Abdo S

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Sep 30, 2023

fantastic

创建者 Tuvshintur L

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Sep 5, 2023

I love it

创建者 Sayak S

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Aug 14, 2023

very nice

创建者 AmirHosein S

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Jul 8, 2023

very good

创建者 Kislay A

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Jul 7, 2023

Excellent

创建者 Jason Y

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Jul 7, 2023

wonderful

创建者 Ehsan F

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Jun 20, 2023

Fantastic

创建者 A7MED F

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Jun 11, 2023

fantastic

创建者 Izuchukwu S M

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Jun 6, 2023

The best!

创建者 Subham R

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May 21, 2023

OP Course

创建者 Yashvardhan S

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May 11, 2023

Excellent

创建者 Bouthaina T

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Apr 30, 2023

thank you

创建者 DEEPAK K

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Apr 25, 2023

Awesome !

创建者 Vannsh

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Mar 29, 2023

very nice

创建者 Sathiyalokeswaran L

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Mar 12, 2023

very good

创建者 Sanket E

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Mar 5, 2023

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Mar 1, 2023

excellent

创建者 Rajesh T

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Feb 28, 2023

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Jan 15, 2023

very nice

创建者 Christian B

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Nov 27, 2022

brilliant

创建者 Le H Q S

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Nov 13, 2022

very good

创建者 Puneet K

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Nov 1, 2022

very good