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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

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.

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.

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5326 - Supervised Machine Learning: Regression and Classification 的 5350 个评论（共 6,053 个）

创建者 partheniac

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Oct 22, 2022

good

创建者 Junping W

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Oct 8, 2022

good

创建者 Garima S

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Oct 7, 2022

NICE

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Oct 2, 2022

good

创建者 West X

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Sep 28, 2022

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Sep 21, 2022

great

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Aug 22, 2022

great

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Jul 31, 2022

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Jun 30, 2022

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Feb 17, 2026

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Feb 12, 2026

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创建者 ME23B1005 G V

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Jan 27, 2026

supe

创建者 Vaibhav M

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Jan 10, 2026

nice

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Jan 2, 2026

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Dec 31, 2025

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Dec 19, 2025

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Nov 26, 2025

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Nov 17, 2025

nice

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Nov 15, 2025

cool

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Sep 23, 2025

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Sep 4, 2025

best

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Aug 19, 2025

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Aug 18, 2025

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