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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

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1376 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 1400 个评论(共 7,283 个)

创建者 Sayar B

Jul 5, 2018

Professor Ng explains complex concepts with such ease. Uses great examples to illustrate the 'why' aspects of everything in this course.

创建者 Rishab R

May 9, 2018

Another excellent course which builds on the material from the previous course.

Thanks Andrew for presenting it in the best way possible.

创建者 Xiaolong L

Feb 27, 2018

Very helpful course. There are a lot of practical tips covered. Also, the explanations to why the techniques could work is very helpful.

创建者 Sami

Feb 15, 2018

very useful course to understand how to tune your algorithm for better results and accuracy, also how to manipulate your hyperparameters

创建者 Boon H T

Feb 5, 2018

Lots to learn about parameters that effect the neural network and various regularization and optimization techniques for neural network.

创建者 Ankur G

Dec 26, 2017

This course provides a lot of information that ML researchers obtain through practice. This course will help beginners get a head start.

创建者 Gek H C

Dec 14, 2017

I love this course. Videos are very well split into short sessions, clear explanation, very good examples, quizzes and graded tutorials.

创建者 Jitendra M

Oct 9, 2017

Andrew Ng has no parallel in bringing absolutely complex concepts down to a level that idiots like me can understand and apply. Salute!

创建者 Kishore V

Sep 2, 2017

Programming assigments guide you through everything you need to know about choosing parameters and implementing optimization algorithms.

创建者 Suzaki Z

Jul 23, 2023

Very helpfull in understanding how the fine tuning and everything works!!

love the way how Mr. Ng explain everything simple and neat....

创建者 Praveen

Jan 18, 2023

This is an excellent course. Well organized with right amount of depth to understand the concepts. Please keep them coming! Thank you!!

创建者 Camilo G

Apr 29, 2021

Me gustó mucho la forma en la que muestran las diferencias entre varias vías a tomar al hacer 'tuning' de los algoritmos.

Lo recomiendo

创建者 Leonardo P

Sep 30, 2020

Really fun and informative, it was so clear I feel I have very good basics and understanding of neural networks structure and creation!

创建者 Hasaan A

Jul 27, 2020

Awesome course that introduces you to tuning hyperparameters, different optimization algorithms and implement most things from scratch.

创建者 Safvan V

Jun 10, 2020

Really interesting content, especially regularization and dropout. We must have to go through this before start implementation of DNN.

创建者 Michael L

Apr 23, 2020

Overall great, very interesting! I think it would be great if you could provide some PDF with material summery in the end of each week.

创建者 Carlos S C V

Apr 14, 2020

Muy buen curso para mejorar las Deep Neural Networks, bien explicado y las tareas ayudan mucho a clarificar su implementación en Python

创建者 Noel J

Apr 10, 2020

Excellent material and even better presentation! Home work assignment are done so well and help you understand the material. Loved it!!

创建者 Jean M C

Mar 14, 2020

Great course. It does use Tensorflow 1.0 though and I do feel like they hold your hand too much during the exercises. Enjoyed it still.

创建者 李子轩

Jan 21, 2020

感谢吴恩达老师带来的课程,这门课不仅仅使我对深度学习更加感兴趣.还让我想到了很多能够用其完成的一些事情. 课程虽然结束了, 但是有关于深度学习的学习才刚刚开始, 最后再次感谢吴恩达老师, 以及提供这个平台的coursera课程,让我在中国可以听到来自全世界的课程,谢谢!

创建者 Renesteban

Jan 20, 2020

Excellent Course, I could go deep into the Machine Learning methodologies and I learned how to optimize Deep Neural Networks Algorithms

创建者 Vignesh S

May 24, 2019

I got to know the optimization algorithms to use and also the Tensorflow programming framework in depth. It was a really useful course.

创建者 Dawid P

Apr 2, 2019

Alot of useful info about neural network tuning and easy introduction to Tensorflow framework. Absolutely must see for every DL novice!

创建者 Hashem A

Jan 17, 2021

Amazing course, with great practical insights on hyperparameter optimization for deep learning models. Andrew Ng is a great professor!