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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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1651 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 1675 个评论(共 7,283 个)

创建者 bardock s

Jun 10, 2020

A very good course on hyper parameter tuning, some notations can be updated as they are confusing in the derivations

创建者 Pramod M N

Jun 5, 2020

A really intuitive course that gives insight into how to optimize deep learning models in the simplest way possible.

创建者 Usama k

May 3, 2020

Awesome Learning Platform with Awesome Trainers and especially the practical work they enable us to do is awesome...

创建者 Simon B C

Apr 30, 2020

As always greate teacher and course! Together with the Machine learning course the best course I've followed so far!

创建者 Karthi K

Dec 17, 2019

Again one more excellent course from Andrew Ng! Great path for mastering Deep Learning! Learnt a lot from Andrew Ng!

创建者 Rishabh M

Dec 8, 2019

Found this to be a tad bit difficult than the others, but great learning and really simple explainations by Prof NG!

创建者 Prashanth S

Nov 24, 2019

Immense amount of learning in these first two courses. Will go over the lectures once again to cement understanding.

创建者 Krishna T T

Nov 23, 2019

One of the best. Having been working with deeplearning for 2 years. Yet i have had some nice pointers in this course

创建者 Seun O

Nov 13, 2019

There is a lot to digest in this course. As always, Andrew did a great justice to every element of the entire course

创建者 Oscar R R M

Aug 26, 2019

Great course, perfect continuation for the machine learning course imparted by the Standford University on Coursera.

创建者 Khursheed A

Apr 2, 2019

Concepts such as dropout, batch norm and exponentially weight averages are explained very well with good intutiions.

创建者 Prafful P

Mar 31, 2019

Great Insights for improving performance of Deep Neural Networks, couldn't find any better resource other than this.

创建者 Cynthia W

Aug 23, 2018

It was pretty tough, lots of content to understand, but the quiz and assignment really helped solidify the concepts

创建者 Sumit K

Aug 14, 2018

Andrew Ng is the Best Instructor to have for deep Learning and related topics. I am impressed by his way of teaching

创建者 Surya T K

Mar 11, 2018

Gives great insights about the importance of parameters in neural networks keeping in view the real time scenarios .

创建者 Pradeep R

Feb 25, 2018

Short but excellent material as usual - and a gentle introduction to TF. Can't wait to learn more from Prof. Andrew.

创建者 karan m

Jan 6, 2018

Explains the things in very good intuitive way and also introduces to basic maths so as to understand things better.

创建者 KAUSHIK N

Nov 8, 2017

Very helpful material for Regularization and Optimization which are one of the most critical parts of Deep Learning.

创建者 Ruoyu ( W

Sep 19, 2017

Very clear, easy to understand. The tutorial of Tensorflow and coding assignment are step by step, smooth to follow.

创建者 Zhao Y G

Sep 14, 2017

It was fun and I learnt a lot in this course such as adjusting the hyperparameters and understanding the optimizers!

创建者 Amit L

Apr 25, 2023

The course introduces great useful tools very clearly and the assignments contributes to the material understanding

创建者 hossein r

Apr 28, 2022

It's really insightful. I wish it has more about Tensorflow and also you can choose between Tensorflow and Pytorch.

创建者 Rajpurohit V

Oct 2, 2020

best course ever, awesome assignment I have created complete optimization algorithm from scratch awesome experience

创建者 Agustin N

Oct 1, 2020

Great course! Easy to follow, and all the importants concepts and topics are covered in an intuitive way. Congrats!

创建者 Aashish S

Jul 4, 2020

Well paced course. I liked the flow of the course especially since the topics were interrelated and organized well.