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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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5001 - Supervised Machine Learning: Regression and Classification 的 5025 个评论（共 6,053 个）

创建者 Luqmaan A

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Sep 3, 2022

masterpeice

创建者 Prathamesh K

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Aug 20, 2022

best course

创建者 Amol A

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Aug 12, 2022

Exceptional

创建者 Mohamed A

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Aug 10, 2022

very useful

创建者 Rowan R

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Nov 25, 2025

Well Done.

创建者 Kevin L

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Nov 12, 2025

impressive

创建者 Khaled E E

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Oct 16, 2025

very great

创建者 Nguyen N H L

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Sep 14, 2025

excellence

创建者 arvind r

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Sep 7, 2025

Best tutor

创建者 Prabir M

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Aug 4, 2025

Insightful

创建者 Neusa M

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Jul 28, 2025

The best !

创建者 Corey V

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Jun 13, 2025

Very good!

创建者 Sahan7

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Jun 8, 2025

good Couse

创建者 ADITYA S K

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Apr 20, 2025

Best ever!

创建者 Ahmet K

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Jan 13, 2025

Inspiring.

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