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学生对 DeepLearning.AI 提供的 Advanced Learning Algorithms 的评价和反馈

4.9
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8,320 个评分

课程概述

In the second course of the Machine Learning Specialization, you will: • Build and train a neural network with TensorFlow to perform multi-class classification • Apply best practices for machine learning development so that your models generalize to data and tasks in the real world • Build and use decision trees and tree ensemble methods, including random forests and boosted trees 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 theoretical 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

Dec 29, 2024

The course provides an excellent introduction to widely used machine learning concepts, including Neural Networks. While the material can be challenging, it is presented in a digestible manner.

HI

Apr 17, 2024

This showcases key points and advice on building a good model via optimizing model hyperparameters hence making the learner able to debug and tune the model for the particular situation.

筛选依据：

1001 - Advanced Learning Algorithms 的 1025 个评论（共 1,241 个）

创建者 Alexander S C C

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Apr 11, 2024

Interesante

创建者 Deepak S m

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Dec 15, 2023

was amazing

创建者 Youssef H

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Oct 12, 2023

Very Useful

创建者 Nihaz N

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Oct 11, 2023

Insightful!

创建者 Muhammad T H

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Sep 25, 2023

Excellent!!

创建者 Amir M

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Jul 23, 2023

Just great!

创建者 Fatemeh J

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Apr 29, 2023

very Good 1

创建者 bounphet t

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Apr 15, 2023

good course

创建者 Arnaud J K K

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Mar 28, 2023

Super cours

创建者 Aniketh N B

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Feb 15, 2023

Good theory

创建者 Kaitlyn H

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Jan 4, 2023

Super Good!

创建者 Vedang B

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Dec 6, 2022

Best Course

创建者 Lê T M D

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Aug 17, 2022

best course

创建者 Karn T

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Jul 10, 2022

Good Course

创建者 Rajeev R

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Jun 20, 2022

Best course

创建者 Valentin N

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Jul 30, 2025

Insightful

创建者 Mohammed B

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Aug 12, 2024

Perfection

创建者 Darshankumar P

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Jan 15, 2024

awesome...

创建者 Jianzong W

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Dec 9, 2023

Excellent!

创建者 Scotley W

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Apr 24, 2023

great info

创建者 Heitor A A M

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Feb 28, 2023

Spetacular

创建者 Aditya R

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Jan 26, 2023

Fantastic!

创建者 Sai R P

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Sep 25, 2022

Great one

创建者 Olivier C

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Sep 26, 2025

Thank you

创建者 Hilal P

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Aug 3, 2025

excellent