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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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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：

4601 - Supervised Machine Learning: Regression and Classification 的 4625 个评论（共 5,932 个）

创建者 Adham A

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Feb 24, 2024

Very helpful <3

创建者 Aqeel I

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Feb 5, 2024

Amazing Lecture

创建者 Sandeep M

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Dec 30, 2023

Great course!!!

创建者 Satyajeet R

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Dec 13, 2023

just phenomenal

创建者 David R

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Sep 8, 2023

excellent intro

创建者 Victor M

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Aug 2, 2023

Muy emocionante

创建者 ahmed k

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Jul 12, 2023

Amazing course!

创建者 אבינעם ב

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Jun 7, 2023

Great course!!

创建者 Đoàn K

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May 27, 2023

greatest course

创建者 Daniel .

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Apr 23, 2023

Amazing course!

创建者 Mostafa S E

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Apr 9, 2023

Amazing course!

创建者 Untitled

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Apr 4, 2023

Awesome course!

创建者 Prakash N

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Feb 27, 2023

amazing course.

创建者 yy

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Feb 17, 2023

Amazing course!

创建者 fernando s

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Feb 13, 2023

excelente curso

创建者 Eldred L

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Jan 12, 2023

Awesome course!

创建者 SUPATH D

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Jan 9, 2023

Awesome Course!

创建者 Radovan M

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Nov 23, 2022

Just fantastic!

创建者 Iandro R

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Nov 17, 2022

Great and clear

创建者 Joshi L

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Oct 28, 2022

Muy buen curso

创建者 anubhavdipsite

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Oct 26, 2022

Amazing course

创建者 Muhammad M

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Sep 14, 2022

Fruitful course

创建者 tariq s

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Sep 10, 2022

perfect course

创建者 Mohamed B

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Sep 6, 2022

very wonderful

创建者 Atharv P

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Sep 5, 2022

awesome course