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学生对 DeepLearning.AI 提供的 Neural Networks and Deep Learning 的评价和反馈

4.9
123,577 个评分

课程概述

In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications. 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

MM

Jun 10, 2020

An excellent introduction to Neural Network and Deep Learning. In particular, I found the insights and analogies shared during the course very useful. Can't wait to complete the next 4 in the series!

HN

Jan 17, 2020

Very structured approach to developing a neural network which I believe I can use as foundation for any project regardless its complexity. Thanks professor Andrew Ng and the team for their dedication.

筛选依据:

5151 - Neural Networks and Deep Learning 的 5175 个评论(共 10,000 个)

创建者 Bobby G P

Feb 18, 2020

It was one of the best course. It has given me boost to complete the remaining courses in deep learning specialization. Thank You coursera and deeplearning.ai

创建者 Siddharth G

Dec 17, 2019

Exactly what I was looking for, This course helped me finally understand what exactly is happening under the hood in Deep learning and helped me implement it.

创建者 Daniel B

Jun 25, 2019

Nice course! Always enjoy Andrew's course. Very nicely and clearly elaborated.

Putting neural network concepts into practice and seeing it do the work is fun!

创建者 Jorge B

Apr 5, 2019

Great course for introducing into neural networks and deep learning. Extremely detailed video lectures and easy to follow instructions during the whole course

创建者 Regi M

Feb 26, 2019

The highlight of the course is the coverage of basic concepts. It motivate students to review these concepts and to understand the working of these algorithms

创建者 Sai V K S

Jan 17, 2019

The notebooks are amazing. The teaching is simple and in depth. The instructor is top class. Overall this course is a must for every deep learning enthusiast.

创建者 Gunarto S N

Dec 5, 2018

Prof. Ng really explains everything clearly and it really helps me to understand the core concept of the deep learning as well as its mathematical foundation.

创建者 MD S I

Nov 20, 2018

Fantastic course !! Please make it free. Add regular practice problems on weekly basis. Arrange competitions regularly on these kind of problems in this site.

创建者 Pablo C E

Aug 15, 2018

Excelente introducion to Deep Learning Networks! Course is carefully well made! Its a privilege to be able to have a course like this available to me! Thanks!

创建者 Sharath K

Aug 13, 2018

This course was excellent in explaining the internal functioning of Neural Networks. I am looking forward to studying the other courses in the specialization.

创建者 Gothireddy y k

Jun 30, 2018

Andrew's courses are very interesting and the experience is amazing, learning the theoretical aspects while practicing made me realize the completeness in it.

创建者 David O P

Apr 13, 2018

Superb course. It has all the important elements:

-Hands on exercises (and with a very good milestone accomplishment guidance)

-Theory well conveyed

-Expert tips

创建者 Federico H

Feb 4, 2018

Fantastic overview with just about the right amount of hand-holding to make it accessible. The level of repetition is great to let concept gradually sink in.

创建者 Clint I

Oct 3, 2017

Solid and accessible overview of deep learning. Calculus for non-calculus types is made highly accessible. Python examples are challenging but easy to follow.

创建者 Federico D M

Sep 14, 2017

Great course. Andre Ng style is fantastic and his approach and his intuitions into math gives you a great understing of what is happening. Highly recommended.

创建者 Federico B

Sep 3, 2017

Excellent course. The material is super clear adn really good to practice. I think having some general idea on deep learning makes the experience even better.

创建者 Shuvendu R

Aug 18, 2017

Please Give me the option for rate this 10 star

The course is just awesome. Anyone can learn a complex subject like deep learning, Andrew Ng has just proved it

创建者 Martin J

Aug 15, 2017

Great introduction and review for me. Set up to learn the basics of NNs. Programming assignments just hard enough and with suggestions/directions that help.

创建者 Kon M

Jun 21, 2023

Course structure is too good to learn from scratch. I have enjoyed the course and assignments as well. Thankyou for the great course and the supportive team.

创建者 Jakeer H

Jun 10, 2022

The first phase of my jurney into the ML/DL domain has been crved so nicedly that I enjoyed each and every lession, quiz, and assignment. Thank you, Coursera

创建者 Khalid W S D

Aug 12, 2021

informative-well written course, gradually presenting the information and requesting the programming assignment for students to involve in the specialization

创建者 Rodrigo A V A

Jun 21, 2021

Love this course. Finally I understood the basic maths for Deep Learning, thanks a lot Andrew! This was that I need it. Looking forward for your next courses

创建者 jean f D

Feb 10, 2021

This training is so interesting.

The teaching method is bright.

Thank you so much.

A proposal : maybe clarify the dictionaries grads, parameters, and cache...

创建者 Иван А Т

Nov 29, 2020

The best course I have ever had on deep learning. Great and clear explanation without difficult mathematics calculations !!! Andrew NG is the best tutor !!!!

创建者 Lucas S M

Sep 20, 2020

Really easy to follow. I particularly liked the intuition videos, such as questioning what each layer actually "sees" as your model processes the input data.