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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.

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3526 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 3550 个评论（共 7,283 个）

创建者 Ruben R R

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Aug 26, 2020

Lots of useful concepts, with hands-on examples!

创建者 Glendon H

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Aug 12, 2020

Thanks Andrew! Your explanations are excellent!

创建者 YounghaeKim

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Jul 25, 2020

Always Thanks to Andrew for high quality course.

创建者 MANOJ K

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May 12, 2020

Great content for beginners and concept focused.

创建者 Haoran L

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Mar 18, 2020

Very concise and informative. Loved the homework

创建者 Carlos A J H

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Feb 7, 2020

Excelent course, as always with professor Andrew

创建者 Mayank A

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Feb 4, 2020

Please provide slides at the end of whole course

创建者 Claudio U R

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Sep 8, 2019

The course helps to implement neural-networks.

创建者 Kseniia P

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Jun 29, 2019

Informative course with well-guided assignments.

创建者 Nicolas D

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Mar 3, 2019

Very nice methodological lesson on deep learning

创建者 Hichem M

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Dec 7, 2018

J'ai beaucoup apprécié ce cours !

it was great !

创建者 narain p

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Nov 24, 2018

it was a very good content to start from scratch

创建者 Ehsan G

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Oct 25, 2018

Last week was so fast, particularly tensor flow.

创建者 Michele C

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Jul 19, 2018

useful, clear and exercises were not frustrating

创建者 RODOLFO X B

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Apr 29, 2018

It is a great course, but you need the first one

创建者 Arun

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Mar 6, 2018

Prof. Andrew Ng has done it again! Great course!

创建者 任宇凡

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Feb 27, 2018

excellent! Informative while easy to understand.

创建者 Giulio T

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Dec 2, 2017

Great insights into the tuning of a Neaural Net!

创建者 Rihab B A

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Nov 25, 2017

Great level of details again Andrew. Keep it up!

创建者 Muhammed B

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Nov 11, 2017

This course is great for hyperparameter tuning .

创建者 Jingbo L

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Oct 22, 2017

Very clear, and gives good points on the basics.

创建者 Robin

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Sep 28, 2017

Nice course for good foundation in deep learning

创建者 Truman P

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Sep 10, 2017

A detailed look into some really practical bits!

创建者 Yongtao M

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Aug 25, 2017

It become more interesting than the first course

创建者 Vishwayishwaran L

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Jul 27, 2024

nice explanations, good course explain strategy