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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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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：

2776 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 2800 个评论（共 7,286 个）

创建者 Jeong W H

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Aug 27, 2023

Please add more lectures for PyTorch too! thank you for great lectures

创建者 Mukesh M

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Mar 22, 2023

Improving Deep Neural Networks, and my understanding of Deep Learning.

创建者 Katlego N

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Feb 28, 2021

Like the Course, wished the dataset to the particle were shared Aswell

创建者 Nils H

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Sep 16, 2020

The Tensor Flow v1 programming assignment should be replaced by v2 one

创建者 ALİ T

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Jul 22, 2020

Best course for researchers, Msc Phd students. Thanks for your effords

创建者 Nick G

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Apr 16, 2020

Very instructive, to learn low-level tecniques for ML usually not seen

创建者 Shivakeshavan

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Apr 15, 2020

It was a useful course but would appreciate more details on Batchnorms

创建者 Dishant S

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Apr 11, 2020

An excellent course covering all the basics and required explanations.

创建者 Juan B T G

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Mar 25, 2020

This course, as part of Deep Learning specialization, is simply great.

创建者 Gourav M

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Jul 15, 2019

Great practice to get hands on programming skills in machine learning!

创建者 Bharat S S

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Jun 3, 2019

Very well organized and delivered in a fantastic way by Professor Ng !

创建者 Elena S

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May 22, 2019

great course! super practical. you learn how to actually work with DNN

创建者 Eric H

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May 18, 2019

Prof Ng is awesome! Teaching you the details of how NN work, and why.

创建者 Siddhant M

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Mar 17, 2019

Really Helpful for strengthening the basics of hyper-parameter tuning.

创建者 Humberto N

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Dec 7, 2018

Great explanation on Hyperparameters, Regularization and Optimization.

创建者 Vova F

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Aug 26, 2018

Excellent. May just as well be the benchmark for all Coursera courses.

创建者 Balázs B

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Jun 2, 2018

Excellent course, providing a great start in practicing deep learning.

创建者 Sanjeev U P

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Apr 22, 2018

Well organized and clearly explained. I finally understand tensorflow.

创建者 Florence C

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Apr 19, 2018

Several important techniques about tuning hyper-parameters were learnt

创建者 Bill R

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Apr 15, 2018

Andrew Ng does a GREAT job of breaking things down and making it easy.

创建者 Amir T K

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Feb 18, 2018

Very very useful and efficient course for starting actual DL projects.

创建者 John C

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Jan 8, 2018

Fantastic coverage of hyperparameter tuning in a deep learning context

创建者 Konstantin Z

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Jan 7, 2018

Practical with lots of helpful tips. Very nice intuitive explanations.

创建者 Samuel Y

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Dec 1, 2017

It would be better to introduce other frameworks as optional material.

创建者 Taehee J

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Nov 28, 2017

This course gets in depth for deep learning based on the first course.