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返回到 Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

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

4.9
63,492 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

AM

Oct 8, 2019

I really enjoyed this course. Many details are given here that are crucial to gain experience and tips on things that looks easy at first sight but are important for a faster ML project implementation

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

筛选依据:

6501 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 6525 个评论(共 7,283 个)

创建者 Samarth B

Sep 11, 2017

Was a great course. Learnt conceptually and implemented Momentum,ADAM & rmsprop. Wish there were more exercises to explore TensorFlow .

创建者 Benjamin J

Oct 29, 2017

I would have liked more programming exercises related to regularization and hyperparameter tuning, but TensorFlow was well introduced.

创建者 ISHAN P

Jun 30, 2021

Weeks 1 and 2 were awesome. However I think we ned a more intensive programing assignment on Week 3 to get hands on with Tensor Flow.

创建者 Paulo M

Aug 26, 2020

I liked the course. I just think there should be more assignments. Perhaps after each week because the content is dense and complex.

创建者 Vighnesh N G

Apr 21, 2020

Too much spoon feeding in the programming exercises, could have asked us to make a model with atleast x accuracy then left us alone.

创建者 Mahesh S P

Apr 17, 2020

This was the toughest course since lot of mathematical, especially statistics back ground is required. However, I could complete it.

创建者 S S

Aug 18, 2022

The course includes lots of information and need focus and concentration.

The Tensorflow part is not enough to solve the assignment.

创建者 Sri K

Apr 10, 2020

Its require basic python programming for implementation of neural networks , different models techniques to get perspective of it .

创建者 Ahmed N

Mar 23, 2018

One of my best courses i have ever participated in, i gained a lot of knowledge and knew the underlying mathematics of every model.

创建者 Mathieu J

Feb 24, 2018

Second step of the specialization,

a bit less rewarding than the fist course as more fine tuning and less overview of deep learning

创建者 Mohammed M

Oct 18, 2017

Programming assignments could have been more challenging. Otherwise, the course instructor is pretty awesome!! Thank you Andrew Ng.

创建者 Swann C

Oct 6, 2017

Good material and definitely essential in order to gain a lot of time aiming at the right direction navigating all these parameters

创建者 Amine D

Nov 22, 2019

Very good course. I would have liked a little longer introduction to the tensorflow architecture and less help on the assignements

创建者 Curt D

Sep 5, 2018

A good introduction to gradient descent algorithms and hyperparameter tuning with a little TensorFlow thrown in for good measure!

创建者 Jorge C

Sep 22, 2017

Good course, Hyperparameter tuning, Regularization and Optimization are well explained, and the Tensor Flow lab is very useful too

创建者 ROBIN

Jun 26, 2025

Très instructif et didactique. Manque juste un support de cours propre pour les formules au lieu de screenshots du tableau blanc.

创建者 Marcela I

Jan 18, 2021

Es un buen curso, basado principalmente en aspectos prácticos. Me pareció menos interesante que otros de la misma especialización

创建者 Xin J X

Sep 19, 2017

Tips are very useful! Have some typos/errors in assignments, more coding work can help understanding. Thanks for sharing, Andrew!

创建者 JUI-CHIEH, W

Aug 26, 2017

Many practical tricks such as tuning hyper parameters and the use of major optimization techniques such as batchnorm and dropout.

创建者 Md. T R

Jul 18, 2020

I think a bit more hands on teaching would be better for this course and also if you could mention resources it would be better.

创建者 Jose G H H

Jan 25, 2022

Bastante bueno, explica de manera simple y práctica los distintos métodos para acelerar el aprendizaje de las redes neuronales.

创建者 Arvind D R

Dec 31, 2021

The last assignment has no clear instructions on how to use the functions and has error which doesn't initazlie the parameters

创建者 a b

Aug 3, 2018

Very interesting course. But a bit fast I would say. Sometimes I didn't feel the programming assignments were that challenging.

创建者 kevin k

Jul 6, 2020

The course was great overall, but I wish we had more involvement in the set up of the programs in the programming assingments.

创建者 NAMAN M

Jun 2, 2020

It would've been much easier if the graded functions of the tensorflow practice assignment would've been explained separately.