Chevron Left
Back to Neural Networks and Deep Learning

Learner Reviews & Feedback for Neural Networks and Deep Learning by DeepLearning.AI

4.9
stars
122,502 ratings

About the Course

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....

Top reviews

NL

Oct 3, 2020

This course helps me to understand the basic concept of Deep Learning. However I think this course should include at least 1 week (or 2-3 videos) about math so learners can have a better understanding

MG

Jul 28, 2020

Pretty well organized with really helpful examples and assignment especially. Definitely made the basis for deep learning algorithms. Looking forward to the next modules and dive deep in this domain.

Filter by:

5276 - 5300 of 10,000 Reviews for Neural Networks and Deep Learning

By 芃維 陳

Oct 18, 2019

Very clair and the homework doesn't need you to have a pretty good level in maths. However if you want to learn it better, I'll still recommand some maths.

By Sayan B

Sep 8, 2019

I applaud the effort and the teaching style of Dr. Andrew Ng and all the others who contributed in the whole materials. Thank you from the bottom my heart!

By VIKASH K C

May 18, 2019

It was the great course i have ever done , (best for the deep Learning course ) ,

Thanks a lot for sir Andrew Ng , you are god of ML and Deep learning !!!!

By Alexander R M

Apr 14, 2019

Very good introduction into NN and DL with good programming exercises to get started

(requires some background knowledge it programming and linear algebra)

By Pedro F

Mar 18, 2019

Fantastic way to learn in building complex neural networks. Step by step, teach us how to implement layers, activation functions, cost functions and so on.

By 董林滔

Nov 25, 2018

本次Andrew为我们带来了更好的神经网络入门课程,相比于《机器学习》课程,该课程的编程作业和课后选择题的题量更大,且jupyter notebook的作业形式使得学生必须过目所有代码,这加深了学生对于神经网络的理解,且jupyter的交互式特性也使得学生能够更快地得到反馈,有利于更好地掌握python编程。

By Mustafa B D

Oct 22, 2018

Really great course for learning essential concepts about neural nets. I only wish the homeworks were harder but they will surely teach you lots of things.

By Hongyi L

Oct 4, 2018

Very clear and good explained lecture, well designed assignment. It really make me understand when I build a deep learning model from scratch all by myself

By Lilly S

Aug 13, 2018

Dr. Ng patiently and thoroughly explains the mathematics and code behind shallow and deep neural networks. A very well-organized course - highly recommend.

By Devesh A

Aug 10, 2018

Incredibly well designed course! I took a lot away from taking it; I definitely recommend this course to people who are interested in deep learning at all.

By Sanjay K

Apr 23, 2018

I have learn basics of neural networks and its working. This specialization is really amazing everyone should take it for better insights of deep learning.

By Frederik C

Apr 19, 2018

Good intuitive explanation of the basic building blocks of deeplearning. The Jupiter notebooks is a nice and useful way to implement python coding without.

By Sumit G

Mar 18, 2018

This course is an excellent starting point. It brings out the motivation and operation of basic Neural Networks in an intuitive manner. Highly recommended.

By Noah D

Jan 17, 2018

Great course! Dr. Ng breaks things down very well and makes sure all the concepts are easily accessible and thoroughly explained for the student. Loved it!

By Maurizio C

Dec 10, 2017

Well explained, flexible on math requirements, exceptionally good exercises on programming - allow you to learn in depth the theory and put it to practice.

By Dan L

Nov 13, 2017

Great course! Well organized materials and super practical problems to work on as programming assignments which just make the learning process so much fun!

By Raj

Nov 5, 2017

Dr. Ng is a great instructor and I'm so glad he launched this specialization. There is no one better than Andrew Ng to teach deep learning, he is the best!

By Robert K

Oct 29, 2017

This was a fantastic journey! I'll definitely follow Deep Learning specialization. The ability to see your results on some real datasets is just fantastic.

By Azamat D

Oct 12, 2017

It was very clear introduction to Neural Networks. If you have a problem with understanding forward/backward propagation methods, so welcome to the course.

By Johan A H

Oct 5, 2017

Very clear and easy to follow. ESPECIALLY for anyone who have been exposed to calculus and linear algebra, although he seems to describe everything needed.

By Enrico D

Oct 1, 2017

Great. In one course you will be able to implement NNs with generic numbers of layers in Python. Andrew is great teacher, I cannot stop watching his videos

By Simon W

Aug 31, 2017

Really good. The final exercises are perhaps a little dumbed down, but overall this is a great course for someone with no prior knowledge of deep learning.

By Poonam L

Aug 22, 2017

Wow it was so detailed and from scratch in python. Videos are so informative . I am gonna keep watching them again and again. Thanks for putting this up.

By liang y

Aug 22, 2017

It is really a good starting point of deep learning. Easy understandable material and bunch of coding assignment for creating a neural network from scratch

By Konpat P

Aug 21, 2017

Highly recommended for those who seek to understand deep (and even shallow) neural network on how to model, how to train, really in matrices computations !