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学生对 DeepLearning.AI 提供的 Supervised Machine Learning: Regression and Classification 的评价和反馈

4.9
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:

3926 - Supervised Machine Learning: Regression and Classification 的 3950 个评论(共 5,932 个)

创建者 Mohamed A

Apr 4, 2024

The best course for this field.

创建者 FEDI L

Mar 22, 2024

Extremely inspiring and helpful

创建者 Peter V E

Mar 19, 2024

Great course! Very well taught.

创建者 Deleted A

Feb 16, 2024

this course is very interesting

创建者 Joseph D

Dec 5, 2023

Very well organized and taught!

创建者 Jimi W

Sep 4, 2023

Everything is explained clearly

创建者 Liaqat N

Sep 2, 2023

It was fun learning this course

创建者 Reza N

Aug 22, 2023

The best course for learning ML

创建者 陈爽羽

Aug 21, 2023

非常棒的一门课,让我初步了解了机器学习,十分感谢各位老师的帮助

创建者 Dilyana D

Aug 1, 2023

Very well paced and structured!

创建者 Nirjara B

Jun 22, 2023

Very good course for beginners.

创建者 Maulaya R

May 20, 2023

Very good mathematical approach

创建者 Ragul A

Apr 9, 2023

Very useful, Easy to understand

创建者 Jihan K

Mar 22, 2023

Complex but interesting course!

创建者 Luc B

Jan 22, 2023

Super formation ! Je recommande

创建者 Vadim P

Jan 7, 2023

Great course, highly recommend.

创建者 Abhay K

Dec 26, 2022

I love Andrew NG teaching style

创建者 Ella N

Nov 18, 2022

simple and fun, smart and clear

创建者 Shuo L

Nov 17, 2022

The explanation is super clear.

创建者 Milos I

Nov 16, 2022

Best specialization on coursera

创建者 Vincent C

Nov 5, 2022

Tremendous course thanks a lot.

创建者 Hamidreza M

Oct 17, 2022

It was a really useful course.

创建者 Sayak H

Oct 5, 2022

excellent and easy explanation

创建者 gautam g

Jul 23, 2022

Excellent course for beginner.

创建者 PhucVTHE161744

Jul 12, 2022

Super useful for beginner in AI