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学生对 DeepLearning.AI 提供的 Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的评价和反馈

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63,493 个评分

课程概述

In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. By the end, you will learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

热门审阅

AA

Oct 22, 2017

Assignment in week 2 could not tell the difference between 'a-=b' and 'a=a-b' and marked the former as incorrect even though they are the same and gave the same output. Other than that, a great course

DD

Mar 28, 2020

I have done two courses under Andrew ng and I am grateful to Coursera for their highly optimised and easily learning course structure. It has greatly help me gain confidence in this field. Thank you.

筛选依据：

3376 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 3400 个评论（共 7,283 个）

创建者 Ignacio A

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May 10, 2020

Es un curso espectacular, super claro y recomendable

创建者 Esther S

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May 7, 2020

I miss the small questions at the end of the videos.

创建者 Anugrah S

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Apr 3, 2020

Videos and Practical Assignments both are impressive

创建者 Deepak S

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Mar 30, 2020

This course has valuable content! Well satisfied. :)

创建者 Bao N

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Mar 26, 2020

Thank you so much for preparing such a good content!

创建者 Francesco

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Mar 24, 2020

The part on optimization algorithms is really great!

创建者 ARCHIT J

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Mar 18, 2020

This course will help to optimize your model quickly

创建者 Albert H M

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Oct 25, 2019

Very deep material and clear explanation. Thumbs up!

创建者 Rushabh A D

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Sep 14, 2019

The last assignment is the Best Intro to Tensorflow!

创建者 José A

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Jul 17, 2019

I love these courses. I recommend them to anyone! :)

创建者 Yelan T

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Jul 16, 2019

This course is amazing! I will recommend my friends!

创建者 Suraj J

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Jan 1, 2019

Andrew Ng. That's all that needs to be said. Thanks.

创建者 Thibault R

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Dec 15, 2018

Thanks you very much, this is really a great course!

创建者 Arnavesh .

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Oct 13, 2018

Great intuitions and explanations by Prof. Andrew Ng

创建者 Thomas S

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Sep 2, 2018

Great for gaining deeper understanding on the topic!

创建者 Javier M M

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May 25, 2018

Worth the time if you're interested in deep learning

创建者 Juan D B

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May 6, 2018

Muy útil para entender cómo tunnear una red neuronal

创建者 王子铭

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Mar 29, 2018

the tensorflow programming exercise is very helpful!

创建者 Rahul G

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Mar 13, 2018

Speechless. The best specialization I have had ever.

创建者 Soumya B

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Mar 5, 2018

A great high level overview of the methods involved.

创建者 Benjamin C - 陈

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Jan 30, 2018

very thorough discussion of tuning and optimization!

创建者 John Y

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Jan 18, 2018

Andrew Ng is one of the best teachers I've ever had!

创建者 Wenzhi

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Dec 20, 2017

Wonderful course! Thank you very much, Prof. Andrew.

创建者 Pamin R

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Nov 10, 2017

Provide a well intuition of the optimization methods

创建者 Ekaterina T

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Nov 8, 2017

Very good for people with some background in Python!