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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
63,489 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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6551 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 6575 个评论(共 7,283 个)

创建者 Vivi M

Oct 29, 2017

I really enjoyed the classes, in the training I would've liked to try and improve the model with all the tools learned

创建者 Amit J

Nov 22, 2019

Great practical insights.

I wish there were programming assignments on "Hyperparameter tuning" and "Batch norm" too.

创建者 Christopher S

Oct 24, 2019

Good intro to the available tools. Very guided course. For concepts to really stick, own projects or courses needed.

创建者 George L

Oct 24, 2018

it's good, but definitely not as good as the first course since Prof. Ng was not very clear on some of the concepts.

创建者 Ruixin Y

Apr 30, 2018

The course itself is great, but the notebook (programming assignment system) is not stable, it's annoying sometimes.

创建者 Péter T

Apr 17, 2018

Useful information, good intuition, but lack of formal results. More homework would improve the learning experience.

创建者 Ashutosh P

Apr 3, 2018

It was a great course. Really well taught by Professor Andrew Ng. Some "from the scratch" coding assignments needed.

创建者 Suresh D

Feb 28, 2018

I hated the tensorflow part though. Would have much preferred it if we could have moved away from jupyter notebooks.

创建者 Webber K

Jan 31, 2025

some codes are outdated, no longer supported in recent framework. forexample, minimize method in tf Adam optimizer.

创建者 Francisco C

Jul 24, 2018

Very good content overall. Very well explained and good examples. Many mistakes in the comments in the assignments.

创建者 Abhinava K

Dec 8, 2017

Content is good, but assignments are not interesting. Some application oriented assignments will be be encouraging.

创建者 Julio T

Sep 7, 2020

Very good course, all relevant and well explained. I think it just needs and update for working with TensorFlow 2.

创建者 manish c

Jan 23, 2020

Like all other andrew ng courses this course is also the best course to deep dive into neural network algorithms .

创建者 Francesco P

Feb 26, 2019

I would like to see more programming assignments. They are very well done and it'd be great to have more of those.

创建者 Angad S

Dec 12, 2017

I would really benefit from this course if more assignments are provided to try different data sets and scenarios.

创建者 Christopher G

Feb 23, 2024

Great course. Some guidance on implementing backpropagation with batch normalization would have been appreciated.

创建者 Rahad A N

May 13, 2020

Absolutely love the course and the way Andrew teaches us, though I have a little bit discomfort in writing codes.

创建者 Emmanuel

Mar 5, 2020

A little bit to theorical and with too many guidance at some points and not much at some other (for TF functions)

创建者 Giovanni C

Feb 11, 2019

I liked the course, but the explanation of tensorflow needs more propaedeutic introduction for a learner like me.

创建者 Charbel J E K

Jan 17, 2018

Really helpful ! Too much concepts to understand but only applying few in the course. I really liked this course.

创建者 Jay R

Dec 23, 2017

Good course to get familiar with hyperparameters and improving the neural networks. And cliff hanger was amazing!

创建者 Mads E H

Oct 26, 2017

Nice and practical. The assignments could go a step further in trying out different things to get better results.

创建者 Jatin K

May 23, 2021

Tensorflow exercise was not good , it could include some basics first. seems like only runnig it for no purpose

创建者 Zechen Y

Apr 12, 2020

The contents are explicit and adequate but I think It would be better if I could get more exercise about coding.

创建者 Jayanthi A

Apr 5, 2018

It was great course, however, I would have liked it to be a lot slower with more time being spent on Tensorflow.