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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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32,078 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

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.

筛选依据：

4201 - Supervised Machine Learning: Regression and Classification 的 4225 个评论（共 6,053 个）

创建者 Ashish k

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May 22, 2025

Great Learning Experience

创建者 Jacques-Antoine D

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Feb 25, 2025

Excellent videos and labs

创建者 Romain D

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Sep 26, 2024

Very clear and insightful

创建者 Pranav S

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Sep 20, 2024

Very quality of knowladge

创建者 prabhjot s

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Jul 22, 2024

excellent teaching skills

创建者 Jatin S

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Jun 30, 2024

Best course for beginners

创建者 Sarthak A

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May 20, 2024

thanku andrew ng for this

创建者 Abdullah D

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Mar 24, 2024

Thank you for everything.

创建者 Avishkar P

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Feb 28, 2024

covers solid fundamentals

创建者 Onkar K

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Feb 5, 2024

Andrew ng is best teacher

创建者 Lakshay S

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Dec 27, 2023

Very well designed Course

创建者 Henrique V D H

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Dec 8, 2023

Great introductory course

创建者 Carlos A

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Sep 6, 2023

Great course! super worth

创建者 KARANAM V K

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Jul 20, 2023

this is avery good course

创建者 Youness E Y

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Jun 21, 2023

Great introduction to ML.

创建者 SJin L

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Jun 4, 2023

Perfect online lecture!!!

创建者 Prateek

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Jun 3, 2023

All very good and useful.

创建者 Afdoni P S

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Apr 7, 2023

yoyoyoyoyooy marveloussss

创建者 Adam d G

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Jan 30, 2023

Great overview of basics.

创建者 Alec P

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Jan 8, 2023

The labs are my favorite!

创建者 Harsh s

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Dec 27, 2022

good understanding course

创建者 Eric T

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Sep 3, 2022

Thank you for the course

创建者 Hyeon Y

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Aug 27, 2022

Great course! Thank you.

创建者 Zeeshan K Y

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Aug 24, 2022

Thank you Deeplearning.ai