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學生對 deeplearning.ai 提供的 Advanced Learning Algorithms 的評價和反饋

4.9
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38 個評分
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6 條評論

課程概述

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....

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MM

2022年6月22日

Excellent course, although it would have been good to talk more about backward propagation, after finishing this course this is the only point that is left unclear in my mind.

WH

2022年6月18日

An excellent update to the previous Machine Learning course. Goes into excellent detail about each algorithm and the practical notebooks are useful and easy to follow.

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1 - Advanced Learning Algorithms 的 11 個評論（共 11 個）

創建者 Mohamed N M

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2022年6月23日

E​xcellent course, although it would have been good to talk more about backward propagation, after finishing this course this is the only point that is left unclear in my mind.

創建者 Changlin F

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2022年6月22日

Seems lacking some mathematical details like how to calculate Backpropagation this time

創建者 rcotta

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2022年6月28日

Course 2 of 3 from the Machine Learning Specialization series. Whoever read my previous course comments will find this may sound repeating, but once again I need to praise Ng's way to explain the topic, which made clear some details - particularly on the decision trees videos - that were not so clear to me, even after a couple of MBA classes about the topic. I do recommend this course.

創建者 Will H

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2022年6月19日

An excellent update to the previous Machine Learning course. Goes into excellent detail about each algorithm and the practical notebooks are useful and easy to follow.

創建者 Davi M

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2022年7月1日

I really enjoy doing this course. Thanks!

創建者 RyounHeo

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2022年7月1日

The best machine learning course!!!

創建者 Hritik A

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2022年7月1日

Watched till week2. Great Content

創建者 Fernando A

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2022年7月1日

Excellent course!

創建者 Rajeev R

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2022年6月20日

Best course

創建者 Raktim M

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2022年6月28日

The content is excellent but some more emphasis must be given on the discussion of the codes in the Jupyter Notebooks otherwise it'll become less appealing to the once who don't have a good grasp over Python.

創建者 Yuriy G

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2022年7月1日

Slightly disappointed with the assignments to be honest, most of them are too easy to solve, and moreover can be just copypasted from the hints.

Great theory which lacks some demanding practice tasks.

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