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

4.9
8,419 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

DG

Apr 14, 2023

Extremely educational with great examples. Helpful to know Python beforehand or the syntax will become a time sync, and understanding the mathematics as going through the class makes it a decent pace.

SB

Nov 6, 2022

This course is a brief but thorough introduction. It has a good mixture of theory and practice.Andrew Ng explains every thing very good, understandable and in a fun way.I highly recommend this class!

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326 - Advanced Learning Algorithms 的 350 个评论(共 1,265 个)

创建者 Srinath J

Dec 28, 2024

thank you Andrew for al the great work that you do and the way you give back is your wonderful great karma and great deeds

创建者 Hamza Z

Jul 21, 2024

A beginner friendly course part of machine learning specialization to gain insights to key algorithms in machine learning.

创建者 Ricardo F d B

Jun 5, 2023

Excellent course. Prof. Ng is very clear in his expositions, with great material to support the course. Highly recommended

创建者 Jose C

Sep 27, 2022

Amazing course! Extremly usefull not only for beginners but for those who already know to code but want to learn about IA

创建者 Sam O T

Mar 25, 2024

The right mix of technical and non-technical information. The introduction of not-so-easy theoretical concepts is gentle.

创建者 Vahid H

Aug 5, 2022

This course is awesome. Why? Because it is very simple but at the same time is complete and to the point. Thanks Andrew.

创建者 Abubakar A

Aug 8, 2024

i just love the content and the occasional jokes thrown into the lectures. Learned alot and enjoyes every moment of it.

创建者 Amith V

Jan 30, 2024

Loved the teaching by instructor never made me feel like i dont know anything thank you sir and the team for this course

创建者 Atharv P

Oct 29, 2023

This course has helped me to get a deep understanding of neural networks as well as various machine learning algorithms.

创建者 Shiva K

Jan 5, 2023

Seriously good but need more math content. Prof Andrew Ng, please include more math derivations and advanced math stuff.

创建者 Katam V K

Jan 1, 2025

There should be some explanation for the labs in the decision trees topic(week 4) apart from that everything is great.

创建者 israel m p

Feb 23, 2023

Es un excelente curso para adentrarse a algoritmos avanzados de Machine Learning. Andrew Ng y su equipo son excelentes.

创建者 Baris B

Jul 13, 2022

Great resource for learning basic concepts of neural networks and decision trees. Thanks a lot for making it available.

创建者 Mohammad Y

Feb 7, 2025

best machine learning instructor ever, I will always be grateful to Mr. Andrew for his huge impact on my academic life

创建者 Shreshtha Y

Jul 8, 2024

Easy to understand and learn from. Only improvement would be to explain xgboost and random forest algorithm a bit more

创建者 Alexander M

Jul 3, 2024

I enjoyed this even more than the previous course in the series and I look forward to unsupervised learning algorithms

创建者 Md. M R

Apr 22, 2024

Instructor like Andrew Ng. sir, blessing now a days.!! Wish to learn from him face to face!! Best course design ever!!

创建者 Francisco S A

Jul 25, 2023

Good compilation of some of the most common advanced learning algorithms. Missing some like SVM but great in any case.

创建者 Kartik A

Aug 7, 2024

Developed a better understanding of machine learning libraries and algorithms along with the mathematics behind them.

创建者 Fangyuan L

Nov 16, 2023

nice instructor and very useful learning materials, the course is also designed to be very begininger level friendly!

创建者 Mamy R

Jul 24, 2023

Very strong learning methodology, from easy understanding to abstract content with enriching practices!

Thanks a lot!

创建者 Shawn B

Aug 15, 2022

Very useful material. I recommend it to everyone interested in learning about practical machine learning algorithms.

创建者 Rizoan H R

Feb 8, 2025

All the best wishes to respected prof. Andrew Ng sir and fellow instructors for creating this masterclass course !

创建者 Damilare L A

Jan 6, 2025

All I needed to learn was met in this course. I am glad I took the course. Thanks DeepLearning.AI, thanks Coursera.

创建者 Simpal K M

May 24, 2023

It was a great course. I am thankful to Andrew Ng and full team who made these difficult concepts a piece of cake.