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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

RR

Jun 12, 2020

Could have increased assignments and some more indepth knowledge of tensorflow and proper installation way of tensorflow cause mine is showing error when iam trying to practice as shown in the video

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:

6626 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 6650 个评论(共 7,286 个)

创建者 Ryan M

Oct 7, 2018

a very informative course, I was introduced to Tensorflow through this course... I absolutely loved it

创建者 Dan C

Feb 28, 2018

I had a bug in my compute_cost function that caused cost to spiral but the grader did not catch it....

创建者 Yash J

May 17, 2020

There should have been deeper explanation for the tensor flow section. Otherwise an excellent course.

创建者 Tim W

Aug 20, 2020

Course material was quite good, only disappointment was that it was taught in tensorflow 1 and not 2

创建者 John C

May 18, 2020

Great instruction on the fundamentals. Probably need to update to Tensorflow 2 or just teach Keras.

创建者 Akshat D

Apr 22, 2020

This was one of the amazing courses I've ever attended on Coursera. Kudos to Andrew NG and the team.

创建者 Sahil A

Mar 11, 2020

week 3 : Tensorflow framework explanation can be much better otherwise the whole course is very good

创建者 Lin Z

Mar 28, 2019

interesting introduction about deep neuro networks with examples on how to use Tensorflow framework.

创建者 Marijan S

Sep 9, 2018

I learned very useful info, but the last programming asignment with tensorflow was a pain in the a**

创建者 Sébastien C

Nov 19, 2020

This is a good overview of optimization techniques. I think the exercises are sometimes too guided.

创建者 Gopal K

Jul 15, 2020

A lot things I got to learn.Also the worksheet were properly designed to clear any doubt if one had

创建者 Apoorv A

Feb 4, 2019

I think things could have been more difficult. Currently it is way to easy to pass the assignments.

创建者 Sajal D

Sep 13, 2020

an awesome course.....one can know more about deep learning from scratch by enrolling this course.

创建者 Potnuru A

Jun 17, 2018

This course provides more tips and ideas toward deep learning and introduces tensorflow. Worth it.

创建者 Faniry R

Mar 13, 2018

Best explanation ever! Exercises should be made available even without a possibility of submission

创建者 Tirumala M

Jan 23, 2018

Well explained the need of regularizations. Also python was best language to get assignments done.

创建者 Siddhi V T

Sep 19, 2019

An awesome course for someone who wants to learn how to tune the hyperparameters of their models.

创建者 Alexey V

Mar 18, 2019

Ran into bugs with some assignments, for example week 7 was not correctly calculating final model

创建者 Tamás J

Jun 14, 2018

Jupiter Notebook fails too offen! I had to close the window, start again, which is very annoying!

创建者 Chen X

Mar 26, 2018

It's fun they assume you know human error rate or optimal Bayesian. It's very rare in real world.

创建者 Alejandro R

Oct 25, 2017

I miss the end of video quizzes, but can't rate it lower than 4 because this course is excellent.

创建者 Prasad D

Jul 1, 2020

Some examples to be solved manually would have helped get a better understanding of the concepts

创建者 Ayushman K

Apr 24, 2020

Learnt a lot of new things. Only complain i have frmo this course is the use of Tensorflow 1.x .

创建者 Digvijay R

Jan 18, 2020

perhaps more practice of tensorflow is required. The tensorflow module also needs to be updated.

创建者 Isaraparb L

Jul 15, 2018

Some of the math may be hard to grasp, but the course gives a lot of useful information overall.