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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：

4926 - Supervised Machine Learning: Regression and Classification 的 4950 个评论（共 5,931 个）

创建者 Daniel M M

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Jan 9, 2025

pragmatico

创建者 Hongyi Y

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Jan 6, 2025

Very good!

创建者 Gavar b

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Oct 17, 2024

next level

创建者 Vladimir M

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Aug 30, 2024

Brilliant!

创建者 Luciana d S E U

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Aug 28, 2024

Very clear

创建者 Guilherme P

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Aug 8, 2024

Very good!

创建者 Anik D B

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Aug 6, 2024

very good!

创建者 Michel B

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May 29, 2024

Good work!

创建者 Michał D

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May 15, 2024

Very good!

创建者 DaxoWiz '

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May 9, 2024

Magnifique

创建者 An N K

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Mar 17, 2024

Meaningful

创建者 Parsa N

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Mar 6, 2024

I love it!

创建者 Ahmed A

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Feb 3, 2024

I love it!

创建者 mojtabacode

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Feb 1, 2024

excellent.

创建者 Zakaria F

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Dec 29, 2023

impressive

创建者 Priyanshu P

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Dec 26, 2023

Amazing!!!

创建者 Szu-Yao C

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Dec 19, 2023

Must Have!

创建者 Claudio M A

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Aug 16, 2023

Excellente

创建者 Bernard A

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Jul 31, 2023

The best !

创建者 Abdul K

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Jul 16, 2023

just great

创建者 Pouria S P

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Jul 16, 2023

perfectily

创建者 Austing D

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Apr 23, 2023

Fantastic!

创建者 Tomas B F A

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Apr 6, 2023

Excellent!

创建者 David D Z

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Mar 18, 2023

Phenomenal

创建者 Md. N S

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Mar 18, 2023

Excellent.