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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
63,507 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

BA

May 31, 2020

Very good course, useful and smart. Some of the example are on tensorflow 1 but I think that they will update them soon to keras tf2 Thank you!I will pass on what I have learned here to undergrads :)

DH

Apr 26, 2020

Everything, Everyparameter in neural networks looks familiar to me now. I feel like I can optimize them for better accuracy. Overall I learned some new things and the way of teaching was really nice.

筛选依据:

3176 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 3200 个评论(共 7,286 个)

创建者 Aditya K

Feb 23, 2020

Wonderful Content , great delivery and amazing assignment.

创建者 Anshuman K

Jan 10, 2020

Well structured, very well explained ... Excellent course!

创建者 Javier S A

Nov 19, 2019

Really good course to improving my skills in deep learning

创建者 Gustavo d P P

Nov 8, 2019

very good course.

The explanations are in an efficient way!

创建者 Javier F

Nov 7, 2019

Excellent! Very clear course. Congratulations to Prof. Ng!

创建者 Madan K

Aug 21, 2019

Introduction to Tensorflow was systematic and educational.

创建者 Chun Y Y

Aug 3, 2019

Interesting course to learn how to optimize your ML model!

创建者 介阳阳

Mar 16, 2019

Thank you for providing such an amazing course! Thank you.

创建者 Ethan ( W

Mar 5, 2019

Great intuition to understand how to improve deep learning

创建者 Ibrahim H

Nov 23, 2018

Very well balance between theory and hands-on assignments.

创建者 鞅骠豪

Dec 22, 2017

质量一贯的好但是就是有点短,希望能加长一下。还有能不能提供如何安装TensorFlow的视频知道我觉得这很关键!!!

创建者 Mathias P

Dec 8, 2017

Thumbs up to Andrew Ng for making the complex more simple.

创建者 Xiaoyang G

Nov 1, 2017

Really helpful course to learn how to tune the parameters.

创建者 Hussein N

Oct 28, 2017

A wonderful overview of hyper parameters and model tuning

创建者 Venkatakrishnan B

Oct 15, 2017

Awesome materials and way of proceeding is simply rocking.

创建者 Ali L

Oct 9, 2017

A must attend course. It was a great review course for me.

创建者 Vibhutha K

Sep 30, 2017

This is a great course to learn tuning of neural networks.

创建者 ni_tempe

Sep 13, 2017

very good course. The programming assignment is very good!

创建者 Edward W

Sep 9, 2017

Learnt a lot and coding assignment is great reference code

创建者 Ruben P

Mar 13, 2022

Great addition to the previous course on neural networks.

创建者 jing h

Oct 10, 2021

very useful contents, the assignments were well designed

创建者 Tin T

Jul 4, 2021

I have learned numerous techniques to optimize DL models.

创建者 Min T K

Dec 16, 2020

This course is really supported for me to do my research.

创建者 Yuvaraj G

Sep 30, 2020

Neat and through explanation of each concept beautifully

创建者 Somnath R

Sep 19, 2020

Really helpful when i solve real world problems using DL.