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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

4.9
63,489 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

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.

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

筛选依据:

1326 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 1350 个评论(共 7,283 个)

创建者 Rodolfo V

Jun 15, 2020

The course need more exercicies with framwork, this is the only thing I could thought to help to make better that amazing course. Thank you

创建者 Ivan G K

May 21, 2020

Learned quite a bit in this course about proper tuning techniques of Neural Networks as well as a pretty decent introduction to Tensorflow.

创建者 Nihila B

May 19, 2020

The lectures were very clear that I now feel like I'm finally getting somewhere towards my career. Thank you for this amazing opportunity.

创建者 Huong H

May 29, 2018

Excellent course! It instructions, the quizzes and the programming exercises are wonderful. They make me to understand the concepts easily.

创建者 Ishwarya M

May 5, 2018

Course if full of rare intuitions you could get only from someone like Andrew Ng. Thank you Andrew & Team for putting this course together.

创建者 pradeep m

Jan 10, 2018

It would be great if the lecture notes in pdf format can be provided at the end of module, as similar to Machine learning course by Andrew.

创建者 Tsang S H

Nov 26, 2017

Hyperparameter tuning usually mentioned in papers without any systemic workflow. But detailed tuning steps are mentioned in this course !!!

创建者 Agam B

Oct 23, 2017

Fun and engaging, and very accessible too! A great overview of various optimization algorithms, and a great introduction to Tensorflow too.

创建者 Pablo V I

Oct 21, 2017

Awesome curse If you want to understand the mathematics behind some deep learning techniques. Highly recommendable curse! Thanks Andrew Ng!

创建者 Rafael A H P

Oct 20, 2017

Very useful. Goes through a lot of recent advances to optimize deep learning performance. The exercises does feel easy and straightforward.

创建者 Pedro H M P

Apr 28, 2020

Curso bem ministrado, com um olhar profundo para o tema. Gostei muito, supriu a necessidade que eu tinha em entender a fundo redes neurais

创建者 Revanth P

Apr 9, 2020

It is a good breakdown and logical progression of the need and evolution of parameters and hyper-parameters. Throughly enjoyed the course.

创建者 Х. А Р

Apr 3, 2020

In spite of my strong mathematical background I found many interesting features for using maths in Deep Neural Networks. Excellent course!

创建者 SHUBHAM E

Mar 15, 2020

Okay with week 1 and week 3 but you need to improve the motive behind presenting week 2. Also what was the purpose of batch normalization?

创建者 Vinicius d A R

May 3, 2019

Excelente curso para um entendimento mais profundo sobre os parâmetros que compõem uma Rede Neural. Parabéns ao mestre e mentor Andrew Ng!

创建者 Arsalan J

Jan 6, 2019

I believe a approach Sir takes while teaching the course makes it comparatively easy to learn the very difficult concept of deep learning.

创建者 Kunihiro O

Dec 22, 2018

very great useful. I want to learn compute science (bachelor's degree)by top 10 of university.

that Mooc is success. I want more learning

创建者 Mukund A

Nov 29, 2018

Awesome! Very helpful & interesting. Looking to take up more courses in future.

Best way explanation. Awesome quiz & programming exercises.

创建者 Deepak S

May 25, 2018

I was excited to learn TensorFlow and this course provides the foundation for that as well as continue the concepts from Course 1

Thank you

创建者 Junde L

Nov 25, 2017

Thank you so much Andrew. This course sharpens my understanding about deep learning, and lets me know the powerful function of Tensorflow.

创建者 Ao X

Nov 1, 2017

Still a good intro course for DP. But most of the techniques are not really based on math but tricks. Maybe it's part of the nature of DP.

创建者 Gustavo S

Nov 1, 2017

Covers optimization algorithms, Minibatch Gradient Descent, with Momentum, Adam, Xavier initialization, etc. Well-structured and objective

创建者 Wessam A

Oct 2, 2017

Real build-up on the great intro course. Gives valuable practical insights on how to use the techniques learned in real life applications.

创建者 R S k

Aug 28, 2023

We learn about all the parameters we use to tune a neural network including learning to use the tensorflow framework. Very uesful indeed.

创建者 IGNACIO H

Jul 25, 2022

Muy buen curso para entender y aplicar herramientas que hacen más eficiente el uso de DNN. Excelente balance entre profundidad y práctica