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

4.9
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31,304 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

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：

4526 - Supervised Machine Learning: Regression and Classification 的 4550 个评论（共 5,931 个）

创建者 Madhu V

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Feb 2, 2024

Excellent course

创建者 Felipe B d S

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Dec 11, 2023

Curso excelente!

创建者 Zhuojin L

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Dec 2, 2023

wonderful course

创建者 M.M. N

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Nov 12, 2023

Very good course

创建者 Alan S

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Nov 10, 2023

Excellent course

创建者 Bassam E

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Oct 21, 2023

Very good course

创建者 Rousyan F Y

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Oct 19, 2023

Goods understand

创建者 Abdullah A

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Oct 10, 2023

Excellent Course

创建者 Ossama A

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Sep 21, 2023

Thank you Andrew

创建者 Anjali B 2

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Aug 21, 2023

very informative

创建者 Ahmed e

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Aug 18, 2023

very good course

创建者 AustEcon

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Aug 14, 2023

Excellent course

创建者 JUNAID F

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Aug 11, 2023

very informative

创建者 mohammadreza e

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Jul 22, 2023

Good intro to ML

创建者 taleb s

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Jul 6, 2023

excellent course

创建者 Isabella I

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Jul 4, 2023

Amazing teacher!

创建者 arash g

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Jun 30, 2023

Andrew is Great.

创建者 Janith M

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Jun 24, 2023

very good course

创建者 Andika R T

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Jun 21, 2023

very good course

创建者 Hayk A

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Jun 11, 2023

Excellent course

创建者 PRABHAT S

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Jun 11, 2023

Awesome course .

创建者 Sadi T

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May 29, 2023

very good course

创建者 Mehedi H N

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May 12, 2023

Best Course Ever